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- item-1 hasContent peter-adolphs.
- 869 creator angus-roberts.
- 869 creator george-demetriou.
- 869 creator haotian-sun.
- 869 creator robert-gaizauskas.
- 869 type InProceedings.
- 869 label "ANNALIST - ANNotation ALIgnment and Scoring Tool".
- 869 sameAs 869.
- 869 abstract "In this paper we describe ANNALIST (Annotation, Alignment and Scoring Tool), a scoring system for the evaluation of the output of semantic annotation systems. ANNALIST has been designed as a system that is easily extensible and configurable for different domains, data formats, and evaluation tasks. The system architecture enables data input via the use of plugins and the users can access the system s internal alignment and scoring mechanisms without the need to convert their data to a specified format. Although developed for evaluation tasks that involve the scoring of entity mentions and relations primarily, ANNALIST s generic object representation and the availability of a range of criteria for the comparison of annotations enable the system to be tailored to a variety of scoring jobs. The paper reports on results from using ANNALIST in real-world situations in comparison to other scorers which are more established in the literature. ANNALIST has been used extensively for evaluation tasks within the VIKEF (EU FP6) and CLEF (UK MRC) projects.".
- 869 hasAuthorList authorList.
- 869 hasTopic Linguistics.
- 869 isPartOf proceedings.
- 869 keyword "Evaluation methodologies".
- 869 keyword "Text mining".
- 869 keyword "Tools, systems, applications".
- 869 title "ANNALIST - ANNotation ALIgnment and Scoring Tool".
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- item-1 hasContent george-demetriou.
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- item-2 hasContent robert-gaizauskas.
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- 87 creator dan-moldovan.
- 87 creator eduardo-blanco.
- 87 creator nuria-castell.
- 87 type InProceedings.
- 87 label "Causal Relation Extraction".
- 87 sameAs 87.
- 87 abstract "This paper presents a supervised method for the detection and extraction of Causal Relations from open domain text. First we give a brief outline of the definition of causation and how it relates to other Semantic Relations, as well as a characterization of their encoding. In this work, we only consider marked and explicit causations. Our approach first identifies the syntactic patterns that may encode a causation, then we use Machine Learning techniques to decide whether or not a pattern instance encodes a causation. We focus on the most productive pattern, a verb phrase followed by a relator and a clause, and its reverse version, a relator followed by a clause and a verb phrase. As relators we consider the words as, after, because and since. We present a set of lexical, syntactic and semantic features for the classification task, their rationale and some examples. The results obtained are discussed and the errors analyzed.".
- 87 hasAuthorList authorList.
- 87 hasTopic Linguistics.
- 87 isPartOf proceedings.
- 87 keyword "Acquisition, Machine Learning".
- 87 keyword "Information Extraction, Information Retrieval".
- 87 keyword "Semantics".
- 87 title "Causal Relation Extraction".
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- item-1 hasContent eduardo-blanco.
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- 870 creator asanee-kawtrakul.
- 870 creator chaveevan-pechsiri.
- 870 creator patcharee-varasai.
- 870 creator thana-sukvari.
- 870 creator vee-satayamas.
- 870 type InProceedings.
- 870 label "Building an Annotated Corpus for Text Summarization and Question Answering".
- 870 sameAs 870.
- 870 abstract "We describe ongoing work in semi-automatic annotating corpus, with the goal to answer why-question in question answering system and give a construction of the coherent tree for text summarization. In this paper we present annotation schemas for identifying the discourse relations that hold between the parts of text as well as the particular textual of span that are related via the discourse relation. Furthermore, we address several tasks in building the annotated corpus in discourse level, namely creating annotated guidelines, ensuring annotation accuracy and evaluating.".
- 870 hasAuthorList authorList.
- 870 hasTopic Linguistics.
- 870 isPartOf proceedings.
- 870 keyword "Corpus (creation, annotation, etc.)".
- 870 keyword "Discourse".
- 870 title "Building an Annotated Corpus for Text Summarization and Question Answering".
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- item-1 hasContent patcharee-varasai.
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