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en_Spacy_Custom_ner2

Token Classification
spaCy
English
Eval Results
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Ybhav14 commited on
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1 Parent(s): 2b25050

Update spaCy pipeline

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Files changed (16) hide show
  1. .gitattributes +2 -0
  2. README.md +56 -0
  3. config.cfg +144 -0
  4. en_Spacy_Custom_ner2-any-py3-none-any.whl +3 -0
  5. meta.json +132 -0
  6. ner/cfg +13 -0
  7. ner/model +0 -0
  8. ner/moves +1 -0
  9. tok2vec/cfg +3 -0
  10. tok2vec/model +3 -0
  11. tokenizer +3 -0
  12. vocab/key2row +1 -0
  13. vocab/lookups.bin +3 -0
  14. vocab/strings.json +2239 -0
  15. vocab/vectors +0 -0
  16. vocab/vectors.cfg +3 -0
.gitattributes CHANGED
@@ -32,3 +32,5 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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  *.zip filter=lfs diff=lfs merge=lfs -text
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  *.zst filter=lfs diff=lfs merge=lfs -text
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  *tfevents* filter=lfs diff=lfs merge=lfs -text
 
 
 
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  *.zip filter=lfs diff=lfs merge=lfs -text
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  *.zst filter=lfs diff=lfs merge=lfs -text
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  *tfevents* filter=lfs diff=lfs merge=lfs -text
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+ en_Spacy_Custom_ner2-any-py3-none-any.whl filter=lfs diff=lfs merge=lfs -text
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+ tok2vec/model filter=lfs diff=lfs merge=lfs -text
README.md ADDED
@@ -0,0 +1,56 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ ---
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+ tags:
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+ - spacy
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+ - token-classification
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+ language:
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+ - en
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+ model-index:
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+ - name: en_Spacy_Custom_ner2
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+ results:
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+ - task:
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+ name: NER
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+ type: token-classification
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+ metrics:
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+ - name: NER Precision
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+ type: precision
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+ value: 0.9911054638
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+ - name: NER Recall
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+ type: recall
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+ value: 0.9961685824
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+ - name: NER F Score
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+ type: f_score
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+ value: 0.9936305732
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+ ---
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+ | Feature | Description |
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+ | --- | --- |
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+ | **Name** | `en_Spacy_Custom_ner2` |
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+ | **Version** | `0.0.0` |
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+ | **spaCy** | `>=3.5.3,<3.6.0` |
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+ | **Default Pipeline** | `tok2vec`, `ner` |
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+ | **Components** | `tok2vec`, `ner` |
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+ | **Vectors** | 0 keys, 0 unique vectors (0 dimensions) |
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+ | **Sources** | n/a |
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+ | **License** | n/a |
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+ | **Author** | [n/a]() |
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+
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+ ### Label Scheme
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+
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+ <details>
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+
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+ <summary>View label scheme (14 labels for 1 components)</summary>
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+
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+ | Component | Labels |
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+ | --- | --- |
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+ | **`ner`** | `BOOK`, `COMODITY`, `CONTAINER COUNT`, `CONTAINER SIZE`, `CONTAINER SIZE-COUNT`, `DESTINATION`, `ENQUIRY`, `HELP`, `INCOTERM`, `KYC`, `ORIGIN`, `SEARCH RATES`, `SHIP`, `SHIPMENT TYPE` |
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+
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+ </details>
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+
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+ ### Accuracy
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+
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+ | Type | Score |
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+ | --- | --- |
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+ | `ENTS_F` | 99.36 |
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+ | `ENTS_P` | 99.11 |
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+ | `ENTS_R` | 99.62 |
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+ | `TOK2VEC_LOSS` | 10283.83 |
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+ | `NER_LOSS` | 72242.77 |
config.cfg ADDED
@@ -0,0 +1,144 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ [paths]
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+ train = "./training_data.spacy"
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+ dev = "./training_data.spacy"
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+ vectors = null
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+ init_tok2vec = null
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+
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+ [system]
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+ gpu_allocator = null
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+ seed = 0
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+
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+ [nlp]
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+ lang = "en"
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+ pipeline = ["tok2vec","ner"]
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+ batch_size = 1000
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+ disabled = []
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+ before_creation = null
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+ after_creation = null
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+ after_pipeline_creation = null
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+ tokenizer = {"@tokenizers":"spacy.Tokenizer.v1"}
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+
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+ [components]
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+
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+ [components.ner]
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+ factory = "ner"
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+ incorrect_spans_key = null
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+ moves = null
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+ scorer = {"@scorers":"spacy.ner_scorer.v1"}
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+ update_with_oracle_cut_size = 100
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+
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+ [components.ner.model]
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+ @architectures = "spacy.TransitionBasedParser.v2"
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+ state_type = "ner"
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+ extra_state_tokens = false
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+ hidden_width = 64
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+ maxout_pieces = 2
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+ use_upper = true
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+ nO = null
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+
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+ [components.ner.model.tok2vec]
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+ @architectures = "spacy.Tok2VecListener.v1"
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+ width = ${components.tok2vec.model.encode.width}
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+ upstream = "*"
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+
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+ [components.tok2vec]
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+ factory = "tok2vec"
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+
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+ [components.tok2vec.model]
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+ @architectures = "spacy.Tok2Vec.v2"
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+
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+ [components.tok2vec.model.embed]
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+ @architectures = "spacy.MultiHashEmbed.v2"
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+ width = ${components.tok2vec.model.encode.width}
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+ attrs = ["NORM","PREFIX","SUFFIX","SHAPE"]
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+ rows = [5000,1000,2500,2500]
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+ include_static_vectors = false
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+
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+ [components.tok2vec.model.encode]
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+ @architectures = "spacy.MaxoutWindowEncoder.v2"
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+ width = 96
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+ depth = 4
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+ window_size = 1
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+ maxout_pieces = 3
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+
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+ [corpora]
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+
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+ [corpora.dev]
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+ @readers = "spacy.Corpus.v1"
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+ path = ${paths.dev}
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+ max_length = 0
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+ gold_preproc = false
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+ limit = 0
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+ augmenter = null
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+
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+ [corpora.train]
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+ @readers = "spacy.Corpus.v1"
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+ path = ${paths.train}
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+ max_length = 0
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+ gold_preproc = false
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+ limit = 0
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+ augmenter = null
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+
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+ [training]
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+ dev_corpus = "corpora.dev"
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+ train_corpus = "corpora.train"
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+ seed = ${system.seed}
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+ gpu_allocator = ${system.gpu_allocator}
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+ dropout = 0.1
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+ accumulate_gradient = 1
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+ patience = 1600
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+ max_epochs = 0
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+ max_steps = 20000
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+ eval_frequency = 200
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+ frozen_components = []
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+ annotating_components = []
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+ before_to_disk = null
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+ before_update = null
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+
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+ [training.batcher]
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+ @batchers = "spacy.batch_by_words.v1"
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+ discard_oversize = false
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+ tolerance = 0.2
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+ get_length = null
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+
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+ [training.batcher.size]
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+ @schedules = "compounding.v1"
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+ start = 100
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+ stop = 1000
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+ compound = 1.001
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+ t = 0.0
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+
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+ [training.logger]
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+ @loggers = "spacy.ConsoleLogger.v1"
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+ progress_bar = false
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+
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+ [training.optimizer]
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+ @optimizers = "Adam.v1"
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+ beta1 = 0.9
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+ beta2 = 0.999
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+ L2_is_weight_decay = true
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+ L2 = 0.01
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+ grad_clip = 1.0
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+ use_averages = false
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+ eps = 0.00000001
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+ learn_rate = 0.001
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+
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+ [training.score_weights]
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+ ents_f = 1.0
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+ ents_p = 0.0
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+ ents_r = 0.0
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+ ents_per_type = null
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+
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+ [pretraining]
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+
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+ [initialize]
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+ vectors = ${paths.vectors}
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+ init_tok2vec = ${paths.init_tok2vec}
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+ vocab_data = null
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+ lookups = null
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+ before_init = null
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+ after_init = null
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+
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+ [initialize.components]
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+
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+ [initialize.tokenizer]
en_Spacy_Custom_ner2-any-py3-none-any.whl ADDED
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meta.json ADDED
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+ {
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+ "lang":"en",
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+ "name":"Spacy_Custom_ner2",
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+ "version":"0.0.0",
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+ "description":"",
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+ "author":"",
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+ "email":"",
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+ "url":"",
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+ "license":"",
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+ "spacy_version":">=3.5.3,<3.6.0",
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+ "spacy_git_version":"Unknown",
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+ "labels":{
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+ "tok2vec":[
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+ "ner":[
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+ "BOOK",
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+ "COMODITY",
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+ "CONTAINER COUNT",
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+ "CONTAINER SIZE",
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+ "CONTAINER SIZE-COUNT",
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+ "DESTINATION",
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+ "ENQUIRY",
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+ "HELP",
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+ "INCOTERM",
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+ "KYC",
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+ "ORIGIN",
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+ "SEARCH RATES",
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+ "SHIP",
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+ "SHIPMENT TYPE"
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+ ]
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+ },
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+ "pipeline":[
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+ "tok2vec",
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+ "ner"
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+ ],
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+ "components":[
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+ "tok2vec",
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+ "ner"
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+ "disabled":[
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+ "performance":{
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+ "ents_f":0.9936305732,
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+ "ents_p":0.9911054638,
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+ "ents_per_type":{
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+ "SEARCH RATES":{
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+ "KYC":{
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+ "CONTAINER COUNT":{
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+ "CONTAINER SIZE-COUNT":{
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+ }
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+ },
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+ "tok2vec_loss":102.8382523687,
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+ "ner_loss":722.4276996157
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+ },
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+ "requirements":[
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+
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+ ]
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+ }
ner/cfg ADDED
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+ {
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+ "moves":null,
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+ "update_with_oracle_cut_size":100,
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+ "multitasks":[
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+ "min_action_freq":1,
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+ "learn_tokens":false,
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+ "beam_width":1,
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+ "beam_density":0.0,
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+ "beam_update_prob":0.0,
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+ "incorrect_spans_key":null
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+ }
ner/model ADDED
Binary file (141 kB). View file
 
ner/moves ADDED
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tok2vec/cfg ADDED
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+ {
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+
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tok2vec/model ADDED
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+ version https://git-lfs.github.com/spec/v1
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+ oid sha256:211fe5fa4283e43ae6b34bffbd19f77e63212df73a934ce5ba9fbebd06b93c5f
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+ size 6009091
tokenizer ADDED
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+ "Should",
855
+ "Singapore",
856
+ "Sokhna",
857
+ "Somethin",
858
+ "Somethin'",
859
+ "Somethin\u2019",
860
+ "South",
861
+ "South Carolina",
862
+ "Spain",
863
+ "Special",
864
+ "Specialized",
865
+ "Sri",
866
+ "St",
867
+ "St.",
868
+ "Supply",
869
+ "Sydney",
870
+ "T",
871
+ "TES",
872
+ "TKD",
873
+ "TMB",
874
+ "TO",
875
+ "TZDAR",
876
+ "Taiwan",
877
+ "Tanzania",
878
+ "Temperature",
879
+ "Tenn",
880
+ "Tenn.",
881
+ "Tennessee",
882
+ "That",
883
+ "That's",
884
+ "That\u2019s",
885
+ "There",
886
+ "There's",
887
+ "There\u2019s",
888
+ "These",
889
+ "They",
890
+ "This",
891
+ "This's",
892
+ "This\u2019s",
893
+ "Those",
894
+ "Tihi",
895
+ "To",
896
+ "Tokyo",
897
+ "Town",
898
+ "Track",
899
+ "Trade",
900
+ "Tuticorin",
901
+ "Tuticorine",
902
+ "Two",
903
+ "Type",
904
+ "Tyre",
905
+ "U",
906
+ "UAE",
907
+ "UNG",
908
+ "UNT",
909
+ "USA",
910
+ "USNYC",
911
+ "Ummqasr",
912
+ "Urgent",
913
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914
+ "V.V",
915
+ "V_V",
916
+ "Va",
917
+ "Va.",
918
+ "Vancouver",
919
+ "Virginia",
920
+ "Vizag",
921
+ "Volume",
922
+ "W",
923
+ "WT",
924
+ "Want",
925
+ "Warehouse",
926
+ "Warehousing",
927
+ "Was",
928
+ "Wash",
929
+ "Wash.",
930
+ "Washington",
931
+ "We",
932
+ "Were",
933
+ "What",
934
+ "What's",
935
+ "What\u2019s",
936
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937
+ "When's",
938
+ "When\u2019s",
939
+ "Where",
940
+ "Where's",
941
+ "Where\u2019s",
942
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943
+ "Who's",
944
+ "Who\u2019s",
945
+ "Why",
946
+ "Why's",
947
+ "Why\u2019s",
948
+ "Wis",
949
+ "Wis.",
950
+ "Wisconsin",
951
+ "Wo",
952
+ "Would",
953
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954
+ "X'xxxx",
955
+ "X++",
956
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957
+ "X.X",
958
+ "X.X.",
959
+ "X.x",
960
+ "X.x.",
961
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962
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963
+ "XDD",
964
+ "XX",
965
+ "XXX",
966
+ "XXXX",
967
+ "XXXX XXXX",
968
+ "XXXX XXXX-XXXX",
969
+ "XYZ",
970
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971
+ "X_x",
972
+ "Xx",
973
+ "Xx'",
974
+ "Xx'x",
975
+ "Xx'xx",
976
+ "Xx.",
977
+ "Xx.X.",
978
+ "XxXX",
979
+ "Xxx",
980
+ "Xxx'x",
981
+ "Xxx.",
982
+ "Xxxx",
983
+ "Xxxx'",
984
+ "Xxxx'x",
985
+ "Xxxx.",
986
+ "Xxxxx",
987
+ "Xxxxx'",
988
+ "Xxxxx'x",
989
+ "Xxxxx-",
990
+ "Xxxxx.",
991
+ "Xxxxx\u2019",
992
+ "Xxxxx\u2019x",
993
+ "Xxxx\u2019",
994
+ "Xxxx\u2019x",
995
+ "Xxx\u2019x",
996
+ "Xx\u2019",
997
+ "Xx\u2019x",
998
+ "Xx\u2019xx",
999
+ "X\u2019x",
1000
+ "X\u2019xxxx",
1001
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1002
+ "YPE",
1003
+ "Yemen",
1004
+ "York",
1005
+ "You",
1006
+ "Z",
1007
+ "ZINC",
1008
+ "Zealand",
1009
+ "Zurich",
1010
+ "[",
1011
+ "[-:",
1012
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1013
+ "[=",
1014
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1015
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1016
+ "\\n",
1017
+ "\\t",
1018
+ "\\x",
1019
+ "]",
1020
+ "]=",
1021
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1022
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1023
+ "^__^",
1024
+ "^___^",
1025
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1026
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1027
+ "_.)",
1028
+ "_<)",
1029
+ "_^)",
1030
+ "__-",
1031
+ "__^",
1032
+ "_\u00ac)",
1033
+ "_\u0ca0)",
1034
+ "a",
1035
+ "a.",
1036
+ "a.m",
1037
+ "a.m.",
1038
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1039
+ "about",
1040
+ "accommodates",
1041
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1042
+ "ach",
1043
+ "ack",
1044
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1045
+ "ade",
1046
+ "aden",
1047
+ "adm",
1048
+ "adm.",
1049
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1050
+ "africa",
1051
+ "age",
1052
+ "ago",
1053
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1054
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1055
+ "air",
1056
+ "aires",
1057
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1058
+ "ak.",
1059
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1060
+ "ala.",
1061
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1062
+ "all",
1063
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1064
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1065
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1066
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1067
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1068
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1069
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1070
+ "and",
1071
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1072
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1073
+ "angeles",
1074
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1075
+ "ant",
1076
+ "any",
1077
+ "ape",
1078
+ "appropriate",
1079
+ "apr",
1080
+ "apr.",
1081
+ "ar.",
1082
+ "are",
1083
+ "ariz",
1084
+ "ariz.",
1085
+ "ark",
1086
+ "ark.",
1087
+ "arrange",
1088
+ "arranged",
1089
+ "arrangement",
1090
+ "arrangements",
1091
+ "arranging",
1092
+ "arries",
1093
+ "artwork",
1094
+ "artworks",
1095
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1096
+ "asa",
1097
+ "ase",
1098
+ "ash",
1099
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1100
+ "ass",
1101
+ "assist",
1102
+ "assistance",
1103
+ "ast",
1104
+ "at",
1105
+ "ate",
1106
+ "att",
1107
+ "aty",
1108
+ "auckland",
1109
+ "aug",
1110
+ "aug.",
1111
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1112
+ "automotive",
1113
+ "ava",
1114
+ "ave",
1115
+ "ays",
1116
+ "b",
1117
+ "b.",
1118
+ "bad",
1119
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1120
+ "ban",
1121
+ "bandar",
1122
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1123
+ "barcelona",
1124
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1125
+ "basandra",
1126
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1127
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1128
+ "because",
1129
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1130
+ "bel",
1131
+ "belongings",
1132
+ "berlin",
1133
+ "bhuj",
1134
+ "ble",
1135
+ "book",
1136
+ "booking",
1137
+ "border",
1138
+ "both",
1139
+ "bout",
1140
+ "br.",
1141
+ "brazil",
1142
+ "bros",
1143
+ "bros.",
1144
+ "buenos",
1145
+ "bul",
1146
+ "buneos",
1147
+ "busan",
1148
+ "buy",
1149
+ "c",
1150
+ "c'm",
1151
+ "c++",
1152
+ "c.",
1153
+ "ca",
1154
+ "cacar",
1155
+ "cal",
1156
+ "calif",
1157
+ "calif.",
1158
+ "callao",
1159
+ "can",
1160
+ "canada",
1161
+ "cape",
1162
+ "car",
1163
+ "care",
1164
+ "cargo",
1165
+ "cause",
1166
+ "cbm",
1167
+ "ce>",
1168
+ "ces",
1169
+ "cfr",
1170
+ "ch.",
1171
+ "chain",
1172
+ "channai",
1173
+ "charges",
1174
+ "chat",
1175
+ "chemical",
1176
+ "chennai",
1177
+ "chicago",
1178
+ "china",
1179
+ "chittagong",
1180
+ "cif",
1181
+ "clearance",
1182
+ "cmb",
1183
+ "cnsgh",
1184
+ "cnsnz",
1185
+ "co",
1186
+ "co.",
1187
+ "cold",
1188
+ "colo",
1189
+ "colo.",
1190
+ "colombo",
1191
+ "come",
1192
+ "commerce",
1193
+ "commodities",
1194
+ "commodities-",
1195
+ "comodity",
1196
+ "complete",
1197
+ "complex",
1198
+ "compliance",
1199
+ "confirm",
1200
+ "conn",
1201
+ "conn.",
1202
+ "consignment",
1203
+ "consolidated",
1204
+ "container",
1205
+ "container count",
1206
+ "container size",
1207
+ "container size-count",
1208
+ "containers",
1209
+ "controlled",
1210
+ "coordination",
1211
+ "corp",
1212
+ "corp.",
1213
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1214
+ "cost",
1215
+ "could",
1216
+ "courier",
1217
+ "coverage",
1218
+ "coz",
1219
+ "cross",
1220
+ "ct.",
1221
+ "cts",
1222
+ "customs",
1223
+ "cuz",
1224
+ "c\u2019m",
1225
+ "d",
1226
+ "d)",
1227
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1228
+ "d-)",
1229
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1230
+ "d.",
1231
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1232
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1233
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1234
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1235
+ "dXx",
1236
+ "d_d",
1237
+ "d_x",
1238
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1239
+ "dam",
1240
+ "dar",
1241
+ "dare",
1242
+ "days",
1243
+ "dd",
1244
+ "dd'X",
1245
+ "dd'XX",
1246
+ "dd'XXX",
1247
+ "dd'x",
1248
+ "dd'xx",
1249
+ "dd'xxx",
1250
+ "dd/dd",
1251
+ "dd/ddXx",
1252
+ "dd/ddxx",
1253
+ "ddXX",
1254
+ "ddXdd",
1255
+ "ddXx",
1256
+ "ddd",
1257
+ "dddd",
1258
+ "ddp",
1259
+ "ddx.x",
1260
+ "ddx.x.",
1261
+ "ddxX",
1262
+ "ddxdd",
1263
+ "ddxx",
1264
+ "de",
1265
+ "dec",
1266
+ "dec.",
1267
+ "ded",
1268
+ "del",
1269
+ "del.",
1270
+ "delhi",
1271
+ "delivery",
1272
+ "den",
1273
+ "der",
1274
+ "destination",
1275
+ "destinations",
1276
+ "details",
1277
+ "dia",
1278
+ "did",
1279
+ "distribution",
1280
+ "dle",
1281
+ "dm.",
1282
+ "do",
1283
+ "document",
1284
+ "documentation",
1285
+ "does",
1286
+ "doin",
1287
+ "doin'",
1288
+ "doing",
1289
+ "doin\u2019",
1290
+ "don",
1291
+ "dr",
1292
+ "dr.",
1293
+ "dra",
1294
+ "dri",
1295
+ "dry",
1296
+ "dubai",
1297
+ "durban",
1298
+ "dx",
1299
+ "dx.x",
1300
+ "dx.x.",
1301
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1302
+ "dxdd\u2019XX",
1303
+ "dxdd\u2019xx",
1304
+ "dxx",
1305
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1306
+ "e's",
1307
+ "e.",
1308
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1309
+ "e.g.",
1310
+ "each",
1311
+ "eb.",
1312
+ "ebr",
1313
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1314
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1315
+ "eds",
1316
+ "eed",
1317
+ "eet",
1318
+ "effects",
1319
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1320
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1322
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1323
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1324
+ "ems",
1325
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1326
+ "en.",
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1329
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1330
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1331
+ "enquiry",
1332
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1333
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1334
+ "ep.",
1335
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1336
+ "equipment",
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1338
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1339
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1340
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1342
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1346
+ "ety",
1347
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1350
+ "expedited",
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+ "export",
1352
+ "express",
1353
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1354
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1355
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1356
+ "f.",
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+ "facilities",
1358
+ "fcl",
1359
+ "feb",
1360
+ "feb.",
1361
+ "feet",
1362
+ "felixstowe",
1363
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1364
+ "filled",
1365
+ "fla",
1366
+ "fla.",
1367
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+ "for",
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+ "fragile",
1370
+ "frankfurt",
1371
+ "free",
1372
+ "freight",
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+ "fresh",
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+ "from",
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+ "frt",
1376
+ "fruits",
1377
+ "ft",
1378
+ "ftl",
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+ "fulfillment",
1380
+ "full",
1381
+ "g",
1382
+ "g.",
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+ "ga",
1384
+ "ga.",
1385
+ "gbo",
1386
+ "gdynia",
1387
+ "ged",
1388
+ "gen",
1389
+ "gen.",
1390
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1391
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1392
+ "ght",
1393
+ "give",
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+ "glassware",
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+ "goin",
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+ "goin'",
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+ "goin\u2019",
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1400
+ "gonna",
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1404
+ "gov.",
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+ "guangzhou",
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+ "h.",
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+ "had",
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+ "hamburg",
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+ "havin'",
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1459
+ "id.",
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1462
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1463
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1469
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1470
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1471
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1472
+ "immediate",
1473
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1474
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1475
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1476
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1477
+ "inc.",
1478
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1479
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1480
+ "ind.",
1481
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1482
+ "indonesia",
1483
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1485
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1486
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1487
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1488
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1491
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1492
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1496
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1500
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1501
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1513
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1514
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1515
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1516
+ "j.",
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1518
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1519
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1520
+ "jan.",
1521
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1522
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1523
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1524
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1525
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1526
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1527
+ "jnpt",
1528
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1529
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1530
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1532
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1533
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1535
+ "jun.",
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+ "k.",
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+ "kan.",
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1543
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1581
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1600
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+ "mbo",
1618
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1619
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1620
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1621
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1622
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1623
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1624
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1625
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1626
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1627
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1628
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1629
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1630
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1631
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1632
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1633
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1634
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1635
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1636
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1637
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1638
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1639
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1640
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1641
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1642
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1643
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1644
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1645
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1646
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1647
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1648
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1649
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1650
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1651
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1652
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1653
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1654
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1655
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1656
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1657
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1658
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1659
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1660
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1661
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1662
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1663
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1664
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1665
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1666
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1667
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1668
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1669
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1670
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1671
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1672
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1673
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1674
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1675
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1676
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1677
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1678
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1679
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1680
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1681
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1682
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1683
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1684
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1685
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1686
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1687
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1688
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1689
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1690
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1691
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1692
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1693
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1694
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1695
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1696
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1697
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1698
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1699
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1700
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1701
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1702
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1703
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1704
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1705
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1706
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1707
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1708
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1709
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1710
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1711
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1712
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1713
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1714
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1715
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1716
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1717
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1718
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1719
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1720
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1721
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1722
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1723
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1724
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1725
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1726
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1727
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1728
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1729
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1730
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1731
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1732
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1733
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1734
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1735
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1736
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1737
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1738
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1739
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1740
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1741
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1742
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1743
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1744
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1745
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1746
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1747
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1748
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1749
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1750
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1751
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1752
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1753
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1754
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1755
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1756
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1757
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1758
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1759
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1760
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1761
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1762
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1763
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1764
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1765
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1766
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1767
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1768
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1769
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1770
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1771
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1772
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1773
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1774
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1775
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1776
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1777
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1778
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1779
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1780
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1781
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1782
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1783
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1784
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1785
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1786
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1787
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1788
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1789
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1790
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1791
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1792
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1793
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1794
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1795
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1796
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1797
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1798
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1799
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1800
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1801
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1802
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1803
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1804
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1805
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1806
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1807
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1808
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1809
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1810
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1811
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1812
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1813
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1814
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1815
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1816
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1817
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1818
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1819
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1820
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1821
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1822
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1823
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1824
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1825
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1826
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1827
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1828
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1829
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1830
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1831
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1832
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1833
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1834
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1835
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1836
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1837
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1838
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1839
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1840
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1841
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1842
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1843
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1844
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1845
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1846
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1847
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1848
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1849
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1850
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1851
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1852
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1853
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1854
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1855
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1856
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1857
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1858
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1859
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1860
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1861
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1862
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1863
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1864
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1865
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1866
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1867
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1868
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1869
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1870
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1871
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1872
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1873
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1874
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1875
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1876
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1877
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1878
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1879
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1880
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1881
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1882
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1883
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1884
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1885
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1886
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1887
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1888
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1889
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1890
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1891
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1892
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1893
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1894
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1895
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1896
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1897
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1898
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1899
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1900
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1901
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1902
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1903
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1904
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1905
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1906
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1907
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1908
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1909
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1910
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1911
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1912
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1913
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1914
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1915
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1916
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1917
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1918
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1919
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1920
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1921
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1922
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1923
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1924
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1925
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1926
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1927
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1928
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1929
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1930
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1931
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1932
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1933
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1934
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1935
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1936
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1937
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1938
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1951
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1952
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1953
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1954
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1955
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1956
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1957
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1958
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1959
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1960
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1961
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1962
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1963
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1964
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1965
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1966
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1967
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1968
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1969
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1970
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1971
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1972
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1973
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1974
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1975
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1976
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1977
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1978
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1987
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1988
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1989
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1990
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1991
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1992
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1993
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1994
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1995
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1996
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1997
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2000
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2001
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2002
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2003
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2004
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2005
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2006
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2007
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2008
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2009
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2010
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2011
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2012
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2013
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2014
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2015
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2016
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2017
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2018
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2019
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2020
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2021
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2022
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2023
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2024
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2025
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2026
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2027
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2028
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2029
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2030
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2031
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2032
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2033
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2034
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2035
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2036
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2037
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2038
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2039
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2040
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2041
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2042
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2043
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2044
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2045
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2046
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2047
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2048
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2049
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2050
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2051
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2052
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2053
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2054
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2055
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2056
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2057
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2058
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2059
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2060
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2061
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2062
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2063
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2064
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2065
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2066
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2067
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2068
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2069
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2070
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2071
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2072
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2073
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2074
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2075
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2076
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2077
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2078
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2079
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2080
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2081
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2082
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2083
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2084
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2085
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2086
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2087
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2088
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2089
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2090
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2091
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2092
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2093
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2094
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2095
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2096
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2097
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2098
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2099
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2100
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2101
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2102
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2103
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2104
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2105
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2106
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2107
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2108
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2109
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2110
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2111
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2112
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2113
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2114
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2115
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2116
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2117
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2118
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2119
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2120
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2121
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2122
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2123
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2124
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2125
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2126
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2127
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2128
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2129
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2130
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2131
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2132
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2133
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2134
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2135
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2136
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2137
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2138
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2139
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2140
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2141
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2142
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2143
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2144
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2145
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2146
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2147
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2148
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2149
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2150
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2151
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2152
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2153
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2154
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2155
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2156
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2157
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2158
+ "z.",
2159
+ "zag",
2160
+ "zealand",
2161
+ "zed",
2162
+ "zil",
2163
+ "zinc",
2164
+ "zurich",
2165
+ "|",
2166
+ "}",
2167
+ "\u00a0",
2168
+ "\u00ac",
2169
+ "\u00ac_\u00ac",
2170
+ "\u00af",
2171
+ "\u00af\\(x)/\u00af",
2172
+ "\u00af\\(\u30c4)/\u00af",
2173
+ "\u00b0",
2174
+ "\u00b0C.",
2175
+ "\u00b0F.",
2176
+ "\u00b0K.",
2177
+ "\u00b0X.",
2178
+ "\u00b0c.",
2179
+ "\u00b0f.",
2180
+ "\u00b0k.",
2181
+ "\u00b0x.",
2182
+ "\u00e4",
2183
+ "\u00e4.",
2184
+ "\u00f6",
2185
+ "\u00f6.",
2186
+ "\u00fc",
2187
+ "\u00fc.",
2188
+ "\u0ca0",
2189
+ "\u0ca0_\u0ca0",
2190
+ "\u0ca0\ufe35\u0ca0",
2191
+ "\u2013",
2192
+ "\u2014",
2193
+ "\u2018",
2194
+ "\u2018S",
2195
+ "\u2018X",
2196
+ "\u2018s",
2197
+ "\u2018x",
2198
+ "\u2019",
2199
+ "\u2019-(",
2200
+ "\u2019-)",
2201
+ "\u2019Cause",
2202
+ "\u2019Cos",
2203
+ "\u2019Coz",
2204
+ "\u2019Cuz",
2205
+ "\u2019HQ",
2206
+ "\u2019S",
2207
+ "\u2019X",
2208
+ "\u2019Xxx",
2209
+ "\u2019Xxxxx",
2210
+ "\u2019am",
2211
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2212
+ "\u2019cause",
2213
+ "\u2019cos",
2214
+ "\u2019coz",
2215
+ "\u2019cuz",
2216
+ "\u2019d",
2217
+ "\u2019em",
2218
+ "\u2019hq",
2219
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2220
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2221
+ "\u2019nuff",
2222
+ "\u2019re",
2223
+ "\u2019s",
2224
+ "\u2019ve",
2225
+ "\u2019x",
2226
+ "\u2019xx",
2227
+ "\u2019xxx",
2228
+ "\u2019xxxx",
2229
+ "\u2019y",
2230
+ "\u2019\u2019",
2231
+ "\u201d",
2232
+ "\u2501",
2233
+ "\u253b",
2234
+ "\u253b\u2501\u253b",
2235
+ "\u256f",
2236
+ "\u25a1",
2237
+ "\ufe35",
2238
+ "\uff09"
2239
+ ]
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vocab/vectors.cfg ADDED
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