Zenodo (CERN European Organization for Nuclear Research), Jan 6, 2020
This project received funding from the European Union's Horizon 2020 research and innovation prog... more This project received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 825182. The information and views set out in this publication are those of the author(s) and do not necessarily reflect the official opinion of the European Union.
In this paper we discuss containers and other general nouns, and develop a proposal for represent... more In this paper we discuss containers and other general nouns, and develop a proposal for representing them in a structured lexicon. We adopt a typed feature structure formalism and show that even in more cases than those mentioned in the literature an underspecification analysis is appropriate. This contributes to the simplification of the lexicon, postulating less lexical rules and avoiding a lot of redundancy. Our main data come from Catalan, but the results are applicable to many other languages (including English). The paper is organised as follows. In section 1 we present the Catalan data. In section 2 we discuss some of the previous proposals. Section 3 is devoted to develop our treatment, which is implemented in LKB. 1 The main conclusions are given in section 4.
We present Evita, an application for recognizing events in natural language texts. Although devel... more We present Evita, an application for recognizing events in natural language texts. Although developed as part of a suite of tools aimed at providing question answering systems with information about both temporal and intensional relations among events, it can be used independently as an event extraction tool. It is unique in that it is not limited to any pre-established list of relation types (events), nor is it restricted to a specific domain. Evita performs the identification and tagging of event expressions based on fairly simple strategies, informed by both linguisticand statistically-based data. It achieves a performance ratio of 80.12% F-measure. 1
The Dictionaries division at Oxford University Press (OUP) is aiming to model, integrate, and pub... more The Dictionaries division at Oxford University Press (OUP) is aiming to model, integrate, and publish lexical content for 100 languages focussing on digitally under-represented languages. While there are multiple ontologies designed for linguistic resources, none had adequate features for meeting our requirements, chief of which was the capability to losslessly capture diverse features of many different languages in a dictionary format, while supplying a framework for inferring relations like translation, derivation, etc., between the data. Building on valuable features of existing models, and working with OUP monolingual and bilingual dictionary datasets, we have designed and implemented a new linguistic ontology. The ontology has been reviewed by a number of computational linguists, and we are working to move more dictionary data into it. We have also developed APIs to surface the linked data to dictionary websites.
In this paper we provide a description of TimeML, a rich specification language for event and tem... more In this paper we provide a description of TimeML, a rich specification language for event and temporal expressions in natural language text, developed in the context of the AQUAINT program on Question Answering Systems. Unlike most previous work on event annotation, TimeML captures three distinct phenomena in temporal markup: (1) it systematically anchors event predicates to a broad range of temporally denotating expressions; (2) it orders event expressions in text relative to one another, both intrasententially and in discourse; and (3) it allows for a delayed (underspecified) interpretation of partially determined temporal expressions. We demonstrate the expressiveness of TimeML for a broad range of syntactic and semantic contexts, including aspectual predication, modal subordination, and an initial treatment of lexical and constructional causation in text.
Building FactBank or How to Annotate Event Factuality One Step at a Time
Springer eBooks, 2017
FactBank is a corpus of news reports containing event mentions annotated with their factuality st... more FactBank is a corpus of news reports containing event mentions annotated with their factuality status—that is, whether they refer to factual situations, possibilities, or events that did (or will) not take place in the world. Annotating this level of information involves challenges of different types concerning the annotation procedure. For example: What is the adequate level of annotation (sentence, clause, lexical unit)? What are the elements involved in the linguistic expression of event factuality and that should thus be accounted for in the annotation scheme? Should it be a text-extent annotation or a classification task? This article presents the methodological decisions adopted for building FactBank and details the different steps of the annotation process. An analysis of the complexity of the data and the annotation results suggests that the methodological framework applied for building FactBank (annotation scheme, set of factuality values, etc.) is adequately rich for expressing the necessary distinctions while, at the same time, simple enough for ensuring coherent data, as attested by the good interannotation agreement scores obtained.
This document provides a survey over vocabularies for language resources and services and sketch ... more This document provides a survey over vocabularies for language resources and services and sketch necessary extensions and the expected contribution of the Prêt-à-LLOD project to their further development for phenomena currently not sufficiently covered. Future updates with respect to this will be documented within Task 5.4.<br> <br> We focus on three main aspects of linguistically analyzed data<br> 1. lexical-conceptual resources, i.e., repositories of terminology, lexical data, translation, and semantics,<br> 2. linguistically annotated data, concerning linguistic analysis of textual or transcribed data, and<br> 3. language resource terminology, i.e., linguistic data categories and metadata<br> <br> For these areas, we describe representative vocabularies from the Linguistic Linked Open Data community (RDF-based vocabularies) as well as other approaches (e.g., ISO TC37 standards), we identify a number of gaps, and we describe ongoing effort...
Effectively managing the collaboration of many annotators is a crucial ingredient for the success... more Effectively managing the collaboration of many annotators is a crucial ingredient for the success of larger annotation projects. For collaboration, web-based tools offer a low-entry way gathering annotations from distributed contributors. While the management structure of annotation tools is more or less stable across projects, the kind of annotations vary widely between projects. The challenge for web-based tools for multi-layer text annotation is to combine ease of use and availability through the web with maximal flexibility regarding the types and layers of annotations. In this chapter, we outline requirements for web-based annotation tools in detail and review a variety of tools in respect to these requirements. Further, we discuss two web-based multi-layer annotation tools in detail: GATE Teamware and WebAnno. While differing in some aspects, both tools largely fulfill the requirements for today's web-based annotation tools. Finally, we point out further directions, such as increased schema flexibility and tighter integration of automation for annotation suggestions.
We present a system for linking dictionaries at the sense level, which is part of a wider program... more We present a system for linking dictionaries at the sense level, which is part of a wider programme aiming to extend current lexical resources and to create new ones by automatic means. One of the main challenges of the sense linking task is the existence of non one-to-one mappings among senses. Our system handles this issue by addressing the task as a binary classification problem using standard Machine Learning methods, where each sense pair is classified independently from the others. In addition, it implements a second, statistically-based classification layer to also model the dependence existing among sense pairs, namely, the fact that a sense in one dictionary that is already linked to a sense in the other dictionary has a lower probability of being linked to a further sense. The resulting double-layer classifier achieves global Precision and Recall scores of 0.91 and 0.80, respectively. 2012 ACM Subject Classification Computing methodologies→ Lexical semantics; Computing met...
We introduce COMO (Compositional Morphosyntactic Ontology), a classification of part-of-speech ca... more We introduce COMO (Compositional Morphosyntactic Ontology), a classification of part-of-speech categories and their associated grammatical features, which aims to be valid across languages of very different typology. The work has been carried out within the context of the Oxford Global Languages programme, which has the goal of developing language knowledge for 100 languages, particularly those under-represented in the digital space. The requirements around this project are: to be able to describe languages of different typeS while respecting their grammatical tradition, and to be able to serve two main use cases that define our typical work, namely, the labelling of linguistic information in lexicographic products, and the provision of support for language processing tools and corpus annotation processes. These requirements determined the conception and design of COMO, created as a reference model within a broader data architecture in order to address issues of syntactic and semant...
Proceedings of the 7th SIGdial Workshop on Discourse and Dialogue - SigDIAL '06, 2006
In this paper we consider the problem of identifying and classifying discourse coherence relation... more In this paper we consider the problem of identifying and classifying discourse coherence relations. We report initial results over the recently released Discourse GraphBank (Wolf and Gibson, 2005). Our approach considers, and determines the contributions of, a variety of syntactic and lexico-semantic features. We achieve 81% accuracy on the task of discourse relation type classification and 70% accuracy on relation identification.
TempEval2: Evaluating Events, Time Expressions and Temporal Relations
... we are investigating whether for some tasks the more precise set of TimeML relations could be... more ... we are investigating whether for some tasks the more precise set of TimeML relations could be ... expression task, focus on the event task, or focus on the four temporal relation tasks. ... of the five languages for which we provide data: English, Italian, Chinese, Spanish, and Korean. ...
1. Introduction Generative Lexicon (GL) is a theory of linguistic semantics which focuses on the ... more 1. Introduction Generative Lexicon (GL) is a theory of linguistic semantics which focuses on the distributed nature of compositional-ity in natural language (Pustejovsky, 1995). Unlike purely verb-based approaches to compositionality, GL attempts to spread the semantic load ...
Zenodo (CERN European Organization for Nuclear Research), Jan 6, 2020
This project received funding from the European Union's Horizon 2020 research and innovation prog... more This project received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 825182. The information and views set out in this publication are those of the author(s) and do not necessarily reflect the official opinion of the European Union.
In this paper we discuss containers and other general nouns, and develop a proposal for represent... more In this paper we discuss containers and other general nouns, and develop a proposal for representing them in a structured lexicon. We adopt a typed feature structure formalism and show that even in more cases than those mentioned in the literature an underspecification analysis is appropriate. This contributes to the simplification of the lexicon, postulating less lexical rules and avoiding a lot of redundancy. Our main data come from Catalan, but the results are applicable to many other languages (including English). The paper is organised as follows. In section 1 we present the Catalan data. In section 2 we discuss some of the previous proposals. Section 3 is devoted to develop our treatment, which is implemented in LKB. 1 The main conclusions are given in section 4.
We present Evita, an application for recognizing events in natural language texts. Although devel... more We present Evita, an application for recognizing events in natural language texts. Although developed as part of a suite of tools aimed at providing question answering systems with information about both temporal and intensional relations among events, it can be used independently as an event extraction tool. It is unique in that it is not limited to any pre-established list of relation types (events), nor is it restricted to a specific domain. Evita performs the identification and tagging of event expressions based on fairly simple strategies, informed by both linguisticand statistically-based data. It achieves a performance ratio of 80.12% F-measure. 1
The Dictionaries division at Oxford University Press (OUP) is aiming to model, integrate, and pub... more The Dictionaries division at Oxford University Press (OUP) is aiming to model, integrate, and publish lexical content for 100 languages focussing on digitally under-represented languages. While there are multiple ontologies designed for linguistic resources, none had adequate features for meeting our requirements, chief of which was the capability to losslessly capture diverse features of many different languages in a dictionary format, while supplying a framework for inferring relations like translation, derivation, etc., between the data. Building on valuable features of existing models, and working with OUP monolingual and bilingual dictionary datasets, we have designed and implemented a new linguistic ontology. The ontology has been reviewed by a number of computational linguists, and we are working to move more dictionary data into it. We have also developed APIs to surface the linked data to dictionary websites.
In this paper we provide a description of TimeML, a rich specification language for event and tem... more In this paper we provide a description of TimeML, a rich specification language for event and temporal expressions in natural language text, developed in the context of the AQUAINT program on Question Answering Systems. Unlike most previous work on event annotation, TimeML captures three distinct phenomena in temporal markup: (1) it systematically anchors event predicates to a broad range of temporally denotating expressions; (2) it orders event expressions in text relative to one another, both intrasententially and in discourse; and (3) it allows for a delayed (underspecified) interpretation of partially determined temporal expressions. We demonstrate the expressiveness of TimeML for a broad range of syntactic and semantic contexts, including aspectual predication, modal subordination, and an initial treatment of lexical and constructional causation in text.
Building FactBank or How to Annotate Event Factuality One Step at a Time
Springer eBooks, 2017
FactBank is a corpus of news reports containing event mentions annotated with their factuality st... more FactBank is a corpus of news reports containing event mentions annotated with their factuality status—that is, whether they refer to factual situations, possibilities, or events that did (or will) not take place in the world. Annotating this level of information involves challenges of different types concerning the annotation procedure. For example: What is the adequate level of annotation (sentence, clause, lexical unit)? What are the elements involved in the linguistic expression of event factuality and that should thus be accounted for in the annotation scheme? Should it be a text-extent annotation or a classification task? This article presents the methodological decisions adopted for building FactBank and details the different steps of the annotation process. An analysis of the complexity of the data and the annotation results suggests that the methodological framework applied for building FactBank (annotation scheme, set of factuality values, etc.) is adequately rich for expressing the necessary distinctions while, at the same time, simple enough for ensuring coherent data, as attested by the good interannotation agreement scores obtained.
This document provides a survey over vocabularies for language resources and services and sketch ... more This document provides a survey over vocabularies for language resources and services and sketch necessary extensions and the expected contribution of the Prêt-à-LLOD project to their further development for phenomena currently not sufficiently covered. Future updates with respect to this will be documented within Task 5.4.<br> <br> We focus on three main aspects of linguistically analyzed data<br> 1. lexical-conceptual resources, i.e., repositories of terminology, lexical data, translation, and semantics,<br> 2. linguistically annotated data, concerning linguistic analysis of textual or transcribed data, and<br> 3. language resource terminology, i.e., linguistic data categories and metadata<br> <br> For these areas, we describe representative vocabularies from the Linguistic Linked Open Data community (RDF-based vocabularies) as well as other approaches (e.g., ISO TC37 standards), we identify a number of gaps, and we describe ongoing effort...
Effectively managing the collaboration of many annotators is a crucial ingredient for the success... more Effectively managing the collaboration of many annotators is a crucial ingredient for the success of larger annotation projects. For collaboration, web-based tools offer a low-entry way gathering annotations from distributed contributors. While the management structure of annotation tools is more or less stable across projects, the kind of annotations vary widely between projects. The challenge for web-based tools for multi-layer text annotation is to combine ease of use and availability through the web with maximal flexibility regarding the types and layers of annotations. In this chapter, we outline requirements for web-based annotation tools in detail and review a variety of tools in respect to these requirements. Further, we discuss two web-based multi-layer annotation tools in detail: GATE Teamware and WebAnno. While differing in some aspects, both tools largely fulfill the requirements for today's web-based annotation tools. Finally, we point out further directions, such as increased schema flexibility and tighter integration of automation for annotation suggestions.
We present a system for linking dictionaries at the sense level, which is part of a wider program... more We present a system for linking dictionaries at the sense level, which is part of a wider programme aiming to extend current lexical resources and to create new ones by automatic means. One of the main challenges of the sense linking task is the existence of non one-to-one mappings among senses. Our system handles this issue by addressing the task as a binary classification problem using standard Machine Learning methods, where each sense pair is classified independently from the others. In addition, it implements a second, statistically-based classification layer to also model the dependence existing among sense pairs, namely, the fact that a sense in one dictionary that is already linked to a sense in the other dictionary has a lower probability of being linked to a further sense. The resulting double-layer classifier achieves global Precision and Recall scores of 0.91 and 0.80, respectively. 2012 ACM Subject Classification Computing methodologies→ Lexical semantics; Computing met...
We introduce COMO (Compositional Morphosyntactic Ontology), a classification of part-of-speech ca... more We introduce COMO (Compositional Morphosyntactic Ontology), a classification of part-of-speech categories and their associated grammatical features, which aims to be valid across languages of very different typology. The work has been carried out within the context of the Oxford Global Languages programme, which has the goal of developing language knowledge for 100 languages, particularly those under-represented in the digital space. The requirements around this project are: to be able to describe languages of different typeS while respecting their grammatical tradition, and to be able to serve two main use cases that define our typical work, namely, the labelling of linguistic information in lexicographic products, and the provision of support for language processing tools and corpus annotation processes. These requirements determined the conception and design of COMO, created as a reference model within a broader data architecture in order to address issues of syntactic and semant...
Proceedings of the 7th SIGdial Workshop on Discourse and Dialogue - SigDIAL '06, 2006
In this paper we consider the problem of identifying and classifying discourse coherence relation... more In this paper we consider the problem of identifying and classifying discourse coherence relations. We report initial results over the recently released Discourse GraphBank (Wolf and Gibson, 2005). Our approach considers, and determines the contributions of, a variety of syntactic and lexico-semantic features. We achieve 81% accuracy on the task of discourse relation type classification and 70% accuracy on relation identification.
TempEval2: Evaluating Events, Time Expressions and Temporal Relations
... we are investigating whether for some tasks the more precise set of TimeML relations could be... more ... we are investigating whether for some tasks the more precise set of TimeML relations could be ... expression task, focus on the event task, or focus on the four temporal relation tasks. ... of the five languages for which we provide data: English, Italian, Chinese, Spanish, and Korean. ...
1. Introduction Generative Lexicon (GL) is a theory of linguistic semantics which focuses on the ... more 1. Introduction Generative Lexicon (GL) is a theory of linguistic semantics which focuses on the distributed nature of compositional-ity in natural language (Pustejovsky, 1995). Unlike purely verb-based approaches to compositionality, GL attempts to spread the semantic load ...
Uploads
Papers by Roser Sauri