Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)
This paper describes an audio and textual dataset of debating speeches, a first-of-a-kind resourc... more This paper describes an audio and textual dataset of debating speeches, a first-of-a-kind resource for the growing research field of computational argumentation and debating technologies. We detail the process of speech recording by professional debaters, the transcription of the speeches with an Automatic Speech Recognition (ASR) system, their consequent automatic processing to produce a text that is more " NLP-friendly " , and in parallel – the manual transcription of the speeches in order to produce gold-standard " reference " transcripts. We release speeches on various controversial topics, each in 5 formats corresponding to the different stages in the production of the data. The intention is to allow utilizing this resource for multiple research purposes, be it the addition of in-domain training data for a debate-specific ASR system, or applying argumentation mining on either noisy or clean debate transcripts. We intend to make further releases of this data in the future.
The language that we produce reflects our personality, and various personal and demographic chara... more The language that we produce reflects our personality, and various personal and demographic characteristics can be detected in natural language texts. We focus on one particular personal trait of the author, gender, and study how it is manifested in original texts and in translations. We show that author's gender has a powerful, clear signal in originals texts, but this signal is obfuscated in human and machine translation. We then propose simple domain-adaptation techniques that help retain the original gender traits in the translation, without harming the quality of the translation , thereby creating more personalized machine translation systems.
This paper describes the participation of Bar-Ilan university in the sixth RTE challenge. Our tex... more This paper describes the participation of Bar-Ilan university in the sixth RTE challenge. Our textual-entailment engine, BiuTee , was enhanced with new components that introduce chaining of lexical-entailment rules, and tackle the problem of approximately matching the text and the hy-pothesis after all available knowledge of entailment rules was utilized. We have also re-engineered our system aiming at an open-source open architecture. BiuTee's performance is better than the median of all-submissions, and outperforms significantly an IR-oriented baseline.
A method for computing similarity between paths includes extracting corpus statistics for triples... more A method for computing similarity between paths includes extracting corpus statistics for triples from a corpus of text documents, each triple comprising a predicate and respective first and second arguments of the predicate. Documents in the corpus are clustered to form a set of clusters based on textual similarity and temporal similarity. An event-based path similarity is computed between first and second paths, the first path comprising a first predicate and first and second argument slots, the second path comprising a second predicate and first and second argument slots, the event-based path similarity being computed as a function of a corpus statistics-based similarity score which is a function of the corpus statistics for the extracted triples which are instances of the first and second paths, and a cluster-based similarity score which is a function of occurrences of the first and second predicates in the clusters.
A method for cross language information retrieval includes receiving an input query which include... more A method for cross language information retrieval includes receiving an input query which includes at least one word in a source language and translating the input query from the source language to a target language to provide a set of translated queries. A set of documents is retrieved from a document collection based on the translated queries. The retrieved documents are translated back into the source language to generate a set of translated documents. An entailment relationship between each of the translated documents and the input query is assessed. The set of translated documents is refined, based on the assessment of the entailment relationship. A subset (or all) of the refined set of translated documents, and/or the target documents to which the translated documents in the subset correspond, is output.
Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)
This paper describes an audio and textual dataset of debating speeches, a first-of-a-kind resourc... more This paper describes an audio and textual dataset of debating speeches, a first-of-a-kind resource for the growing research field of computational argumentation and debating technologies. We detail the process of speech recording by professional debaters, the transcription of the speeches with an Automatic Speech Recognition (ASR) system, their consequent automatic processing to produce a text that is more " NLP-friendly " , and in parallel – the manual transcription of the speeches in order to produce gold-standard " reference " transcripts. We release speeches on various controversial topics, each in 5 formats corresponding to the different stages in the production of the data. The intention is to allow utilizing this resource for multiple research purposes, be it the addition of in-domain training data for a debate-specific ASR system, or applying argumentation mining on either noisy or clean debate transcripts. We intend to make further releases of this data in the future.
The language that we produce reflects our personality, and various personal and demographic chara... more The language that we produce reflects our personality, and various personal and demographic characteristics can be detected in natural language texts. We focus on one particular personal trait of the author, gender, and study how it is manifested in original texts and in translations. We show that author's gender has a powerful, clear signal in originals texts, but this signal is obfuscated in human and machine translation. We then propose simple domain-adaptation techniques that help retain the original gender traits in the translation, without harming the quality of the translation , thereby creating more personalized machine translation systems.
This paper describes the participation of Bar-Ilan university in the sixth RTE challenge. Our tex... more This paper describes the participation of Bar-Ilan university in the sixth RTE challenge. Our textual-entailment engine, BiuTee , was enhanced with new components that introduce chaining of lexical-entailment rules, and tackle the problem of approximately matching the text and the hy-pothesis after all available knowledge of entailment rules was utilized. We have also re-engineered our system aiming at an open-source open architecture. BiuTee's performance is better than the median of all-submissions, and outperforms significantly an IR-oriented baseline.
A method for computing similarity between paths includes extracting corpus statistics for triples... more A method for computing similarity between paths includes extracting corpus statistics for triples from a corpus of text documents, each triple comprising a predicate and respective first and second arguments of the predicate. Documents in the corpus are clustered to form a set of clusters based on textual similarity and temporal similarity. An event-based path similarity is computed between first and second paths, the first path comprising a first predicate and first and second argument slots, the second path comprising a second predicate and first and second argument slots, the event-based path similarity being computed as a function of a corpus statistics-based similarity score which is a function of the corpus statistics for the extracted triples which are instances of the first and second paths, and a cluster-based similarity score which is a function of occurrences of the first and second predicates in the clusters.
A method for cross language information retrieval includes receiving an input query which include... more A method for cross language information retrieval includes receiving an input query which includes at least one word in a source language and translating the input query from the source language to a target language to provide a set of translated queries. A set of documents is retrieved from a document collection based on the translated queries. The retrieved documents are translated back into the source language to generate a set of translated documents. An entailment relationship between each of the translated documents and the input query is assessed. The set of translated documents is refined, based on the assessment of the entailment relationship. A subset (or all) of the refined set of translated documents, and/or the target documents to which the translated documents in the subset correspond, is output.
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