Commit
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988bfac
1
Parent(s):
66c9e8c
Update app.py
Browse files
app.py
CHANGED
@@ -12,7 +12,6 @@ nltk.download('punkt')
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# load the spacy model
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spacy.cli.download("en_core_web_sm")
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spacy.cli.download("en_core_web_lg")
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# use spacy small because in that way we are closer to a BOW model which is the one we care in our case since we just compare words
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nlp = spacy.load('en_core_web_sm', disable=["parser", "ner"])
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@@ -24,6 +23,7 @@ def find_comptives_symbols(sentence):
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If more than one symbols exist, return []
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"""
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pattern = r"(?<![<=>])[%s](?![<=>])" % (re.escape("<=>"))
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matches = re.findall(pattern, sentence)
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@@ -38,7 +38,7 @@ def find_comptives_symbols(sentence):
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def find_comptives_straight_patterns(sentence):
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"""
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Function to identivy mentions of
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"""
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doc = nlp(sentence)
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@@ -113,7 +113,6 @@ def find_comptives_straight_patterns(sentence):
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return comparatives
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-
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# helper functions for 'identify_pattern_bigger_smaller'
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def identify_comparison(sentence):
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@@ -319,7 +318,7 @@ def find_equal_to_comptives_ngrams(sentence):
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similarity = sentence_ngram_doc.similarity(emb_ref)
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if similarity >= max_similarity:
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possible_reference_list.append({'comparative': [sentence_ngram_str,
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break
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# if we have found a possible refernce that is similar enough with an n-gram of the input sentence, return the comparative '=', otherwise return 0
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@@ -329,6 +328,7 @@ def find_equal_to_comptives_ngrams(sentence):
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return []
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def single_verb_comptives(sentence):
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"""
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This function takes a sentence and identifies any mention of bigger than, smaller than, equal to, expressed
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@@ -363,10 +363,22 @@ def single_verb_comptives(sentence):
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break
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elif any(lemma in equal_references_sg for lemma in syn.lemma_names()):
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# print(lemma)
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equal_list.append({'comparative': [token.text, "="]})
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break
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final_list = bigger_list + smaller_list + equal_list
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if final_list:
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@@ -503,6 +515,7 @@ def multiword_verb_comptives(sentence):
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return bigger_l + smaller_l + equal_l
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def identify_comparatives(sentence):
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"""
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This function combines the results of all the aforementioned techniques (simple and advance) to identify bigger than, smaller than, equal to patterns
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@@ -535,55 +548,74 @@ def identify_comparatives(sentence):
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return unique_output
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def magnitude_binding(sentence):
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comparative_symbols = find_comptives_symbols(sentence)
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comparative_mentions = identify_comparatives(sentence)
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if len(comparative_symbols) == 1:
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else:
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return 0
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return 0
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from transformers import pipeline
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import gradio as gr
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title = "
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description = "This is a simple demo just for demonstration purposes
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examples = [
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["
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["earthquake located in
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["
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["earthquake located in
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["earthquake located in
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["I want an earthquake that
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["I want an earthquake that
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["I want an earthquake that
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["I want an
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]
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gr.Interface(
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fn=
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inputs="text",
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outputs="text",
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title=title,
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# load the spacy model
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spacy.cli.download("en_core_web_sm")
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# use spacy small because in that way we are closer to a BOW model which is the one we care in our case since we just compare words
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nlp = spacy.load('en_core_web_sm', disable=["parser", "ner"])
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If more than one symbols exist, return []
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"""
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# symbols regex pattern
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pattern = r"(?<![<=>])[%s](?![<=>])" % (re.escape("<=>"))
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matches = re.findall(pattern, sentence)
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def find_comptives_straight_patterns(sentence):
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"""
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Function to identivy mentions of comparatives. The form is "comparative adverbs/adjectives followed by than", "words like more/less followed by than", "equal to"
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"""
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doc = nlp(sentence)
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return comparatives
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# helper functions for 'identify_pattern_bigger_smaller'
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def identify_comparison(sentence):
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similarity = sentence_ngram_doc.similarity(emb_ref)
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if similarity >= max_similarity:
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possible_reference_list.append({'comparative': [sentence_ngram_str, "="]})
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break
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# if we have found a possible refernce that is similar enough with an n-gram of the input sentence, return the comparative '=', otherwise return 0
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return []
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def single_verb_comptives(sentence):
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"""
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This function takes a sentence and identifies any mention of bigger than, smaller than, equal to, expressed
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break
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elif any(lemma in equal_references_sg for lemma in syn.lemma_names()):
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equal_list.append({'comparative': [token.text, "="]})
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break
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# for syn in synsets:
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# antonyms = syn.lemmas()[0].antonyms()
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# if antonyms and any(lemma in bigger_references_sg for lemma in antonyms[0].name()):
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# return 0
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# elif antonyms and any(lemma in lesser_references_sg for lemma in antonyms[0].name()):
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# return 0
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# elif antonyms and any(lemma in equal_references_sg for lemma in antonyms[0].name()):
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# return 0
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final_list = bigger_list + smaller_list + equal_list
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if final_list:
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return bigger_l + smaller_l + equal_l
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def identify_comparatives(sentence):
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"""
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This function combines the results of all the aforementioned techniques (simple and advance) to identify bigger than, smaller than, equal to patterns
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return unique_output
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def comparatives_binding(sentence):
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try:
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comparative_symbols = find_comptives_symbols(sentence)
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comparative_mentions = identify_comparatives(sentence)
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# starting with the symbols, if one was captured
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if len(comparative_symbols) == 1:
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# if the rest of the functions are empty (meaning that there are no other references)
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if len(comparative_mentions) == 0:
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return comparative_symbols
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else:
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return (0, "COMPARATIVES", "more_comparatives_mentions")
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# in case that there is no symbol
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elif len(comparative_symbols) == 0:
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# we need only one mention of comparatives
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if len(comparative_mentions) == 1:
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return comparative_mentions
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# case of no comparative mentions
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elif len(comparative_mentions) == 0:
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return (0, "COMPARATIVES", "no_comparatives")
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# case of no more than one comparative mentions
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else:
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return (0, "COMPARATIVES", "more_comparatives_mentions")
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# case of multiple symbol references
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else:
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return (0, "COMPARATIVES", "more_symbol_comparatives")
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except:
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return (0, "COMPARATIVES", "unknown_error")
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from transformers import pipeline
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import gradio as gr
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title = "Comparatives Demo"
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description = "This is a simple demo just for demonstration purposes for Serco team, to validate the results of the Natural Language module concerning comparatives identification, while in progress"
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examples = [
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["I want an earthquake that is located in Rome, Italy on 01/01/23 with magnitude > 6.2"],
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["I want an earthquake that is located in Rome, Italy on 01/01/23 with magnitude = 6.2"],
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["I want an earthquake that is located in Rome, Italy on 01/01/23 with magnitude bigger than 6.2"],
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["I want an earthquake that is located in Rome, Italy on 01/01/23 with magnitude more than 6.2"],
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["I want an earthquake that is located in Rome, Italy on 01/01/23 with magnitude higher than 6.2"],
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["I want an earthquake that is located in Rome, Italy on 01/01/23 with magnitude smaller than 6.2"],
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["I want an earthquake that is located in Rome, Italy on 01/01/23 with magnitude lesser than 6.2"],
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["I want an earthquake that is located in Rome, Italy on 01/01/23 with magnitude equal to 6.2"],
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["I want an earthquake that is located in Rome, Italy on 01/01/23 with magnitude equivalent to 6.2"],
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["I want an earthquake that is located in Rome, Italy on 01/01/23 with magnitude surpassing 6.2"],
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["I want an earthquake that is located in Rome, Italy on 01/01/23 with magnitude lagging of 6.2"],
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["I want an earthquake that is located in Rome, Italy on 01/01/23 with magnitude that matches 6.2"],
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["I want an earthquake that is located in Rome, Italy on 01/01/23 with magnitude that is superior of 6.2"],
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["I want an earthquake that is located in Rome, Italy on 01/01/23 with magnitude that is inferior of 6.2"],
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["I want an earthquake that is located in Rome, Italy on 01/01/23 with magnitude that is in line with 6.2"]
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]
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gr.Interface(
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fn=comparatives_binding,
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inputs="text",
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outputs="text",
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title=title,
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