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train_95700 | For this reason, in computer science automatic image annotation has been studied for some time now (Jeon, Lavrenko and Manmatha, 2003;Li and Wang, 2008). | its collaborative annotation framework follows a client/server architecture, which facilitates the work of multiple users on consistent data sources. | neutral |
train_95701 | We also release analogical clusters and analogical grids produced from a parallel corpus on 11 European languages using this Python module. | all of these procedures are performed seamlessly to the users by the Words2Grids program. | neutral |
train_95702 | These examples of role language were also found in translated novels 8 but were used less than in Japanese novels. | these cases cannot be categorized into detailed age groups. | neutral |
train_95703 | It supports various types of text format including plain text and CoNLL format. | span is represented as a page number, positions, and its label, while relation contains a page number, connection type, two identified spans and its label. | neutral |
train_95704 | The paper is organized as follows. | following this track, we have laid the foundations for an annotation language that is compatible with Legal-RuleML (Nazarenko et al., 2016). | neutral |
train_95705 | We first observe that there are inconsistencies at the token level since not all instances of an event are always annotated as such. | it uses a variety of sources for its data, including WSJ news. | neutral |
train_95706 | Figure 3 summarizes the document intersections of these three corpora and related ones. | many multi-token events in FB are composed of numbers in combination with symbols (#), currencies ($, us$, c$ ) and percentages (%). | neutral |
train_95707 | Space correction based on learning To correct the spaces within multi-token words based on learning methods, a model was trained to find words with multiple parts separated by spaces. | for this reason, we collected a list of verb roots in past tense and present tense forms. | neutral |
train_95708 | Moreover, even using a language-specific tokenizer might not always solve this problem, because some tokenization ambiguities cannot be solved other than by an arbitrary choice depending on interpretation; for instance, the documentation about the way tokenization is carried out for French in the UD2 corpus mentions that: "This tokenizing and segmentating choice is arbitrary and other French treebanks could choose to do otherwise." | many NLP shared tasks nowadays provide datasets annotated with the linguistic information relevant to the task, so that participants can focus on the core aspects of the task rather than spend time on non-essential pre-processing steps. | neutral |
train_95709 | The mentioned cases are just few examples to show how complex the Arabic lemmatization is, and reveal that many cases should be considered in addition to stripping words from prefixes and suffixes to get their proper lemmatization. | for example, stem patterns for broken plurals are different from their singular patterns, e.g. | neutral |
train_95710 | While BLEU is designed to benefit from multiple reference translations (Papineni et al., 2002), this is a luxury rarely afforded to the modern system, and both of the major MT workshops use single-reference BLEU to evaluate all their tasks 34 . | many of our translations are crowdsourced, and there are no guarantees on the fluency of the participants. | neutral |
train_95711 | and affective (e.g., negative and positive emotions) properties. | the b5-post subcorpus -containing Facebook status updates -is a textual base developed primarily for the purpose of personality recognition and author profiling in Portuguese. | neutral |
train_95712 | Other possible applications include the use of the annotated data for classification algorithms (e.g., to predict a topic category given a letter) or a part-of-speech tagger for historical text. | note that the measurements include an automatic modernization layer for lemmas, implemented using look-up on an authoritative source (de Vries and te Winkel, 1998). | neutral |
train_95713 | Variation is influenced by linguistic contexts as well as sociolinguistic factors (e.g., intended audience). | as administrator of the region, Hooft was responsible for the implementation of this law. | neutral |
train_95714 | Therefore, the percentages mentioned above are approximate and the observations need to be confirmed in future research. | intra-speaker variation in speech corpora (Schilling-Estes, 2002;Szmrecsanyi, 2005) or intra-author variation in English literature (Leech, 1969;Busse, 2002). | neutral |
train_95715 | Note that in Algorithm 1 the first direction is implemented as a special case of the second direction (i.e., skipping 0 tokens). | this preliminary quantitative analysis is consistent with the idiom hypothesis, although other hypotheses might explain the observations equally well. | neutral |
train_95716 | The task of constructing the corpus and selecting the core vocabulary was performed according to the following procedures: 1. | 1 It has many grammatical mistakes and you cannot understand the meaning. | neutral |
train_95717 | In [0.7, 0.8], there was a tendency to simplify only one word. | according to the standard of the Japanese Language Proficiency Test (called JLPT) Level 3 (level of understanding elementary Japanese), it is necessary to master 1,500 words. | neutral |
train_95718 | Nevertheless, Classical Chinese is largely neglected, mainly owing to its obsoleteness. | it's worth studying it. | neutral |
train_95719 | Hence, we have attributes like prompt adherence here, rather than word choice. | one common feature that all the above work has in common is the fact that the essay grading dataset that they used was the ASAP AEG dataset. | neutral |
train_95720 | Each prompt was split into sets of 100 essays each, with the assumption that a set would correspond to a week's worth of time for the annotator. | this is mainly because source-dependent essays are highly dependent on the source text, while argumentative / persuasive essays can utilize arguments from beyond the scope of any text, and so, those arguments have to be coherent and cohesive. | neutral |
train_95721 | The corpus contains texts that could be collected in electronic format only, involving no OCR of scanned paper printed books. | ), • diacritics insertion in the texts that lacked them or diacritics replacement (when non-standard ones occurred). | neutral |
train_95722 | BioRo corpus contains, excluding the punctuation, 9,864,707 tokens distributed in different medical subdomains such as: diabetes, endocrinology, cardiology, oncology, neurology etc. | the POS tagging accuracy for the general purpose Romanian language is over 98% (tufis, 1999), and for the biomedical domain the accuracy is 97.83% (Mitrofan and Ion, 2017). | neutral |
train_95723 | The Romanian language is an under-resourced language, regarding resources available for bioNLP. | we presented the BioRo corpus which contains morphosyntactically annotation. | neutral |
train_95724 | Research effort in the recognition of affect in text has focussed to a large extent on recognition of positive/negative sentiment, while more nuanced emotion representation models have received relatively little attention. | beyond simple positive/negative sentiment, there are two main emotion representation schemes that have been used in automated emotion recognition research. | neutral |
train_95725 | Code-mixing provides some challenges for language identification like spelling variations and non-grammatical structures in a sentence (Barman et al., 2014). | last line determines the category in which the tweet belongs i.e. | neutral |
train_95726 | In this study, we constructed a dialogue corpus for persuasive dialogue systems via crowdsourcing, including the labeling of emotional states and the acceptance of users' utterances. | if there are small mismatches between the desire and the belief, the model evokes a positive emotion such as "happy" or "contentment". | neutral |
train_95727 | This makes the generation of future updates straightforward upon improving the quality of the resources. | each lemma-POS pair is associated with three sentiment scores (positive, negative and objective), in addition to the english gloss. | neutral |
train_95728 | When evaluated on the PATB test set, SentiArabic achieves an accuracy of 76.7% and a weighted F-score of 76.5%. | we find the increase insignificant given the computational overhead incurred by MADAMIRA, which is in favor of the lightweight SentiArabic analyzer. | neutral |
train_95729 | anger, happiness, neutral, etc. | as shown in this paper, there is a strong correlation between the amount of context and the performance of an emotion recognition system despite of the amount of data i.e. | neutral |
train_95730 | The delay between an actual change of emotional behaviour and the moment it is annotated is called reaction lag (RL). | this methodology may lead to a loss of information contained in annotator's perception of emotions. | neutral |
train_95731 | Your task is to identify the emotions that the art evokes, that is, all emotions that the art brings to mind. | the WikiArt Emotions Dataset is made freely available for educational purposes and to facilitate research in emotions, art, human psychology, and automatic image analysis/generation. | neutral |
train_95732 | Many extra emotions were entered by the annotators, including uncertainty, amusement, and jealousy. | these annotations will help test the hypothesis that art that depicts the left side of a person's face or body is on average found to be more appealing (left-cheek bias) (Powell and Schirillo, 2011;Blackburn and Schirillo, 2012). | neutral |
train_95733 | (Fleiss' κ calculates the extent to which the observed agreement exceeds the one that would be expected by chance (Fleiss, 1971). | we chose a somewhat generous aggregation criteria: if at least 40% of the responses (four out of ten people) indicate that a certain emotion applies, then that label is chosen. | neutral |
train_95734 | • To conduct experiments to determine what characteristics of images make them particularly evocative. | a number of museums now have a substantial online presence. | neutral |
train_95735 | HLN is used in SemEval 2007, task 14. | we only compare our results with systems, which reported their results on EK6. | neutral |
train_95736 | Such substitutes can easily be extracted from electronically published educational medical textbooks. | the problems we address here are often deeply rooted in national legal systems world-wide and reflect fundamental economic as well as social concerns (Mittelstadt and Floridi, 2016). | neutral |
train_95737 | The context captured in the features is very limited and usually includes only the current word and a preceding and following word. | this must be verified on a case-by-case basis and it is achieved when an author is able to put their personal stamp onto the work through free and creative choices. | neutral |
train_95738 | Consequently, it should not come as a surprise that the right of translation was the first right to be included in the minimum standard of protection in the oldest copyright international treaty, the Berne Convention. | 5(1), which covers acts of temporary reproduction, only exempts the activities listed in points 1) to 4) above, whereas the activity of point 5), i.e. | neutral |
train_95739 | Most of the texts that can be found online do not carry any licence at all or are part of commercial offers which do not permit reproduction. | the real test is that of the author's own intellectual creation. | neutral |
train_95740 | Figure 2 shows a sample of feature values generated by the Stanford NER. | the SA clause that applies in the present scenario requires that distribution of the adapted material be made under the terms of the same licence or a later version with the same terms. | neutral |
train_95741 | set of texts) that is similar to the corpus to which it is later applied; i.e., it must be of the same language and domain or text type and annotated with the appropriate labels, e.g., "English", "Social Sciences", "scholarly publications" and "named entities" (NE), respectively. | it is important to determine whether the trained model is an adaptation of the original annotated corpora. | neutral |
train_95742 | shows a portion of the LAPPS Grid Galaxy interface and a workflow in which a tokenizer and part-ofspeech tagger from WebLicht are invoked, followed by a named entity recognizer from the LAPPS Grid. | conversion from LIF to TCF requires mapping character offset anchors to each token element, and conversion in the reverse direction demands recomputing offsets from the primary source. | neutral |
train_95743 | The scheme of Fluid Annotation comprised of three main components: DeepLexicon, Fluid Segmentation & Tagger, and Annotation UI ( Figure 1). | different segmenters differs on the particular algorithms they implemented. | neutral |
train_95744 | While Hungarian can be considered an under-resourced language it does have an active and cooperating language technology community which has been developing various tools to cover the basic text processing steps. | it takes the text and the list of analytical modules that the user wants to run as input and provides GATE generated XML containing the annotations as output. | neutral |
train_95745 | Word embedding models can be used to satisfy recurrent tasks in NLP such as lexical and semantic generalisation in machine learning tasks, finding similar or related words and computing semantic relatedness of terms. | jOBIMTEXT is a semantic similarity tool that implements its own algorithm named joBim (Biemann et al., 2013 Table 1: List of functionalities and framework coverage. | neutral |
train_95746 | In addition to the vector file, INDRAINDEXER also generates a metadata file containing all the parameters from both the preprocessing and generation steps. | building and consuming specific word embedding models require the setting of a large set of configurations, such as corpus-dependant parameters, distance measures as well as compositional models. | neutral |
train_95747 | To faciliate error analysis, one of the authors then coded each homograph as either morphosyntactic, lexical, or mixed; the counts of these three categories are given in Table 1. | rule-based components represent substantial barriers for both quality control and internationalization. | neutral |
train_95748 | Since the output of a normalizer is the input of the next normalizer, each bar is as long as the non-rejection part of the bar above it. | while the individual actions performed on the string are expressed as Thrax grammars, the string variation normalizer allows us to specify them without context. | neutral |
train_95749 | (2016), Zhang and Lapata (2017) reformulate this approach in the form of neural encoder-decoder models. | we then chose at most 15 instances for a random selection of modifiers from each band for inclusion in the final dataset, which contains a total of 3632 instances: ROCStories -3026 instances. | neutral |
train_95750 | The best overall stemmer is Ljubešić and Pandžić's stemmer for Croatian, although the optimal stemmer of Kešelj and Šipka is a close second. | the proposed negation-marking technique is found beneficial on the word2vec baseline. | neutral |
train_95751 | The effects of various morphological normalization techniques on STS model performances have also been evaluated. | this effect was also evident when applying POSt StSS to data in English (Batanović and Bojić, 2015), and was previously noted by other researchers as well (Wiemer-Hastings, 2004 table 6: StS model performances on 10-fold CV content and are therefore assigned a lower weight, most often in the 0.7 -0.9 range. | neutral |
train_95752 | For the sake of standardization, we chose to follow the annotation methodology established in the SemEval STS tasks, and we adopted the scoring scheme (a 0 -5 Likert scale) and the general annotation guidelines used therein . | lInSTSS generally achieves results similar to POST STSS, but the POS-TF STSS mixture model performs better than both lInSTSS and POST STSS independently. | neutral |
train_95753 | The optimal string similarity weight in the basic Islam and Inkpen approach tends to be 0.7, resulting in an optimal semantic similarity weight of 0.3. | most of this development has been limited to English. | neutral |
train_95754 | When annotating atomic phenomena, our experts identified and annotated the type, the scope, and in some paraphrase types, the key element. | when the annotation process involves more than two annotators, we first calculate the pairwise TPO measure between any two annotators and then we use one of three different techniques for calculating the overall agreement for the corpus. | neutral |
train_95755 | The meanings of "beat" and "battled" are similar, and play the same syntactic and discourse role in the structure of the texts. | the annotation process included three expert linguists and covered the whole 5801 text pairs from the MRPC corpus. | neutral |
train_95756 | People make assertions on a controversy (or controversial issue) both in the physical world and on social media. | participants were presented with four assertions at a time and asked two questions: 1. which of the assertions they support the most (or oppose the least), 2. which of the assertions they oppose the most (or support the least). | neutral |
train_95757 | To calculate these scores, we reuse the formula shown in equation 2. | these approaches focus on identifying sentiment, stance, claims, premises, reasons, arguments, sentiment, etc. | neutral |
train_95758 | From the agreement judgments, we created the agreement matrix AM , which contains one column per assertion, and one row per participant. | guns should be legal for everyone. | neutral |
train_95759 | The second goal of this work is to summarize information about controversial issues without necessarily being dependent on the described crowdsourcing. | the crowdsourced data will serve as a source of reference (gold) labels for the evaluation of these NLP algorithms. | neutral |
train_95760 | Since it is difficult to give a numerical score indicating the degree of support or degree of opposition, we will give you four assertions at a time, and ask you to indicate to us: -Which of the assertions do you support the most (or oppose the least)? | individual participants were free to judge as many assertions as they wished. | neutral |
train_95761 | #NAME? | during collection, the data was not sampled on the basis of language and so it included data from English, Hindi as well as some other Indian languages. | neutral |
train_95762 | While most of these behaviour like bullying or hate speech have predated the Internet, the reach and extent of the Internet has given these an unprecedented power and influence to affect the lives of billions of people. | there is hardly any theoretical insight into the structure and formation of such behaviours (some notable exceptions include Hardaker, 2010Hardaker, , 2013, in general, and absolutely nothing in Indian scenario. | neutral |
train_95763 | The verb extend (in the sense "extend an offer") seems not to fit the pattern; without the Entity Offered/PAT being a noun phrase meaning exactly what the class is about, namely offers, bids, aid, etc., its meaning is more similar to "hand over" than to "offer". | 500 classes), we will compare the results with automated synonym discovery methods, such as (van der Plas et al., 2011;van der Plas et al., 2014), either using Deep Learning (looking, e.g., at embeddings based on argument-role mapping) or other previously well-researched methods, such as the LDA which has been already used for Czech, e.g., in (Materna, 2012). | neutral |
train_95764 | It is a manually annotated Czech-English valency lexicon linking verbal entries of PDT-Vallex and EngVallex. | from the example below, it is clear that the translation was quite adequate and thus make available should be kept in the synonym class OffER (see the deep dependency annotation of this example captured in figure 2) where the Recipient is annotated with the relation BEN as a dependent on available, denoted as Eff(BEN) in this is considered pure nominalization (other sentences have been found where offer, bid, etc. | neutral |
train_95765 | We will measure this by looking at a target word's relation set, for instance its synonyms, and top n-most-similar words based on the embeddings model. | for the general domain, there exists a wide range of gold standard resources for evaluating distributional semantic models in their ability to capture semantic relations of different types, for instance, Simlex-999 (Hill et al., 2015). | neutral |
train_95766 | We explored three alternative levels of morphological term representations, surface form, lemma, and multiple lemmas, all complemented by the clustering of morphological variants. | in addition, we performed an error analysis and found that 62% of the related terms groups were indeed irrelevant. | neutral |
train_95767 | In addition, we performed an error analysis and found that 62% of the related terms groups were indeed irrelevant. | since these terms do not appear in Hebrew WordNet, they were counted as false positives and decreased the overall MAP. | neutral |
train_95768 | The BHC will be both lemmatized and POS-tagged by using TreeTagger (Schmid 1994(Schmid , 1995 or Frog (Avontuur et al. | an investigation in the 1980s into phonological change in West Frisian and Dutch of (the same) West Frisian speakers, suggests that, at least at the phonological level, the opposite holds: younger speakers were more likely to keep the phonological rules of the two languages apart; whereas older speakers were more likely to confuse them in either language (van der Kuip 1986, Feitsma et al. | neutral |
train_95769 | The gaps between these anchor points are then filled using BLEU-based and lengthbased heuristics. | secondly, we use English-to-Portuguese model to translate the machine translated English sentences into Chinese output. | neutral |
train_95770 | However, Chinese and Portuguese belong to distinct language families (Sino-Tibetan and Romance, respectively) and only a relative much smaller proportion of people have bilingual proficiency of the language pair. | for instance, we could train a SMT system on the sub-corpus in newswire domain and use the system to translate sentences for translation based alignment method. | neutral |
train_95771 | As shown in Figure 1, there is usually a language switch button on the top of a web page which can be used to extract its corresponding page in the other language. | as shown in Table 5, the pivot-based systems perform poor than those trained on direct parallel corpora. | neutral |
train_95772 | Each image comparison HIT showed a single sentence with the possible images below it. | (2010) for the PASCAL Data Set (Everingham et al., 2011), which consists of 5000 descriptive sentences, 5 cap- • The large prawn is on top of the stool. | neutral |
train_95773 | The oracle system evaluation is reported in table 3. | the framework is evaluated using French broadcast news drawn from the REPERE corpus. | neutral |
train_95774 | The second one consists of asking a human to correct the output of the first part. | there are two possible strategies to measure the action duration: 1. using the average of time of annotators having the same experience; 2. using the average of time of annotators having several experiences. | neutral |
train_95775 | Figure 2 clearly shows the difference between the behavior of the TE label prediction model trained on the SNLI corpus and the model trained on the SICK corpus. | hypothesis sentences of the SNLI corpus have a hidden bias to allow prediction of their TE labels without premise sentences. | neutral |
train_95776 | In fact, results are mostly lower for the Croatian than for the English, with the exception of one case: fastText-Skip for WordSim-353. | the difference in English (Germanic language) and Croatian (Slavic language) morphology is huge. | neutral |
train_95777 | Excluding relations of place and time (which may apply to static or dynamic scenes), these fall under the CONFIG-URATION portion of the supersense hierarchy. | in this paper, we show that a tagset for broad-coverage semantic annotation of prepositions and postpositions can be applied-mostly as is-to English possessive constructions. | neutral |
train_95778 | In the LCC dataset, the word pair structure of tariffs is scored as a "3" (high metaphoricity), and this is a reasonable metaphoricity score; clearly, a tariff cannot have a physical structure. | in this work, we describe a new, large dataset (18,000+ instances) annotated for metaphor novelty, built on top Baseline Description RANDOM Predicts a random continuous value in the range of 0-3 for each instance. | neutral |
train_95779 | Brain and Language, 107(1):1 -10. | its novelty score should be low. | neutral |
train_95780 | The first experiment aims to estimate the fraction of spurious sense clusters, the second one evaluates the quality of the post-processed hypernyms. | of related ambiguous terms (Biemann and Riedl, 2013); 2word sense induction via clustering of ego networks (Widdows and Dorow, 2002;Everett and Borgatti, 2005) of related words using the Chinese Whispers graph clustering algorithm (Biemann, 2006); (3) disambiguation of related words and hypernyms. | neutral |
train_95781 | Swampillai and Stevenson (2010) identify nearly 28.6% of the relations appearing across sentences in the MUC6 dataset. | given the above three strands of research related to the field of relation extraction, it can be clearly noticed that significantly a large number of studies have focused on intrasentence relation extraction in comparison to the research work on inter-sentence relation extraction. | neutral |
train_95782 | Our dataset is created following the distant supervision approach. | previous studies on inter-sentence relation extraction have employed smaller datasets (Swampillai and Stevenson, 2010;D'Souza and Ng, 2014;Gu et al., 2017). | neutral |
train_95783 | However, the study is focused on a specialised domain such drug-gene interaction. | further, let us also assume that e 1 is included in a sentence s i and e 2 is included in a sentence s j . | neutral |
train_95784 | There were also other relations that had lesser than 1500 sentence pairs, which are not listed in Table 2, as we do not include those relations in the dataset. | the performance obtained using BIL-STM does not provide a statistically significant improvement against the other examined models. | neutral |
train_95785 | Nevertheless, as we discuss in Sections 2 and 3, diacritics restoration (also known as diacritics generation or diacritization) is an active problem also in many languages with substantially lower diacritics appearance. | in recent years, deep neural networks have shown remarkable results in many areas. | neutral |
train_95786 | From the directed graph A, a Minimum Spanning Tree (MST) is constructed, using Chu-Liu-Edmonds algorithm (Chu & Liu, 1965;Edmonds, 1967) where the weight of each edge is 1/|V|. | at the opposite pole, the literature domain, even if it does not contain long sentences, raises the most parsing problems: the authors' creativity manifests both in the sentence structure (dislocated arguments, unlexicalised ones, unusual word order, etc.) | neutral |
train_95787 | Ellipsis is an important challenge for natural language processing systems, and addressing that challenge requires large collections of relevant data. | table 2 gives the distribution of these data points by the (Fernández et al. | neutral |
train_95788 | The majority baseline results are shown in Table 8. | it has a very low recall when identifying None type sluices. | neutral |
train_95789 | We establish several strong baselines for the emotion detection task on dialogues, and motivate an automatic metric to benchmark progress. | recently, emotion recognition researches on text focus on the learning-based methods. | neutral |
train_95790 | The EmotionPush chat logs are from private conversations. | we adopted Fleiss' kappa to measure the agreement among annotators of the labeling task of the dataset. | neutral |
train_95791 | Those utterances with more than two different emotions voted were put into the non-neutral category. | within a dialogue, there is a high probability of inter-dependency with respect to their sentimental clues. | neutral |
train_95792 | The IT environments typically used in research institutions (operating systems, programming languages, software libraries, database systems, etc.) | 3 this also has unwanted side-effects; First, it means that many posts are annotated only according to one particular category, i.e., the data sets for the categories are mostly disjoint and consequently separate classification models must be trained, rather than a single multi-label model. | neutral |
train_95793 | We gave the developers a month to find contributors and collect judgments, and we paid them awards for successfully building applications and for the quantity and quality of judgments that they submitted. | we chose to collect judgments on the toxicity of Wikipedia discussion comments, where a "toxic" comment is defined as any kind of hateful, aggressive, or disrespectful comment that is likely to make someone leave a discussion. | neutral |
train_95794 | These new configurations outperform both the baseline systems (jv and su) and their performance is tied with the Indonesian system (the differences with Indonesian are not statistically significant). | similarly, we used the Javanese and sundanese multi-speaker corpora individually to construct single-language (but multispeaker) systems jv and su, which serve as baselines in our experiments. | neutral |
train_95795 | Thus, useful feedback consists of clear reasoning and objective evidence supporting factual claims (Park et al., 2015). | we restrict the notion of verifiability to pieces of evidence that may be available at the time the claim is made; predictions about future are considered unverifiable. | neutral |
train_95796 | Having many specific premises, a subset of which may not be present in the text, makes it difficult for manual annotation and automatic classification. | many comments are not written this way, thwarting the government agencies' effort to communicate with citizens. | neutral |
train_95797 | Subject-matter RST Relations and Argument Schemes. | "Admittedly they do not generally prevent you from catching a virus"). | neutral |
train_95798 | • Other clues: the premise contains adjectives or other linguistic items which qualify something as more or less good • Inferential rules: if something is of important value, it should not be terminated if something has a positive value, it should be supported/continued/promoted/maintained if something has positive effects, it should be supported/continued/promoted/maintained if something has a negative effect it should be terminated These two argument schemes are perceived as similar due to the common reference to intentionality and to the frame of human action. | a complete list of the inferential rules is available in the annotation guidelines. | neutral |
train_95799 | Generally, the automatic search for arguments encompasses the following steps (Peldszus and Stede, 2013): 1. the segmentation of texts into argumentative discourse units(ADUs); 2. the classification of the role (e.g., claim, premise) played by each ADU; 3. the analysis of the relations linking ADUs (e.g., support, attack); and 4. the identification argument schemes, namely the implicit and explicit inferential relations within and across ADUs. | they have been conceived as arguments which support the negation of the proposition functioning as claim. | neutral |
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