Overview of the TREC 2006 Question Answering Track
Page 1. Overview of the TREC 2006 Question Answering Track Hoa Trang Dang1, Jimmy Lin2, and Diane... more Page 1. Overview of the TREC 2006 Question Answering Track Hoa Trang Dang1, Jimmy Lin2, and Diane Kelly3 1National Institute of Standards and Technology Gaithersburg, MD 20899 [email protected] 2University of Maryland College Park, MD 20742 [email protected] ...
In this paper we present a maximum entropy Word Sense Disambiguation system we developed which pe... more In this paper we present a maximum entropy Word Sense Disambiguation system we developed which performs competitively on SENSEVAL-2 test data for English verbs. We demonstrate that using richer linguistic contextual features significantly improves tagging accuracy, and compare the system's performance with human annotator performance in light of both fine-grained and coarse-grained sense distinctions made by the sense inventory.
We present a class-based approach to building a verb lexicon that makes explicit the close associ... more We present a class-based approach to building a verb lexicon that makes explicit the close association between syntax and semantics for Levin classes. We have used Lexicalized Tree Adjoining Grammars to capture the syntax associated with each verb class and have augmented the trees to include selectional restrictions. In addition, semantic predicates are associated with each tree, which allow for a compositional interpretation.
Page 1. Sense Tagging the Penn Treebank Martha Palmer, Hoa Trang Dang, Joseph Rosenzweig Universi... more Page 1. Sense Tagging the Penn Treebank Martha Palmer, Hoa Trang Dang, Joseph Rosenzweig University of Pennsylvania 200 South 33rd Street, Philadelphia, PA, USA fmpalmer, htd, [email protected] Abstract ...
This paper describes an hierarchical approach to WordNet sense distinctions that provides differe... more This paper describes an hierarchical approach to WordNet sense distinctions that provides different types of automatic Word Sense Disambiguation (WSD) systems, which perform at varying levels of accuracy. For tasks where fine-grained sense distinctions may not be essential, an accurate coarse-grained WSD system may be sufficient. The paper discusses the criteria behind the three different levels of sense granularity, as well as the machine learning approach used by the WSD system.
We present an approach to building a verb lexicon compatible with WordNet but with explicitly sta... more We present an approach to building a verb lexicon compatible with WordNet but with explicitly stated syntactic and semantic information, using Levin verb classes to systematically construct lexical entries. By using verb classes we capture generalizations about verb behavior and reduce the effort needed to construct the lexicon. The syntactic frames for the verb classes are represented by a Lexicalized Tree Adjoining Grammar augmented with semantic predicates, which allows a compositional interpretation.
Investigations into the Role of Lexical Semantics in Word Sense Disambiguation
Verbs that can have more than one meaning pose problems for Natural Language Processing (NLP) app... more Verbs that can have more than one meaning pose problems for Natural Language Processing (NLP) applications. While homonyms (words with unrelated meanings) are fairly tractable, polysemous verbs with similar related meanings pose the greatest hurdle for automatic Word ...
In this paper we report on our experiments on automatic Word Sense Disambiguation using a maximum... more In this paper we report on our experiments on automatic Word Sense Disambiguation using a maximum entropy approach for both English and Chinese verbs. We compare the difficulty of the sensetagging tasks in the two languages and investigate the types of contextual features that are useful for each language. Our experimental results suggest that while richer linguistic features are useful for English WSD, they may not be as beneficial for Chinese.
In this paper we specifically address questions of polysemy with respect to verbs, and how regula... more In this paper we specifically address questions of polysemy with respect to verbs, and how regular extensions of meaning can be achieved through the adjunction of particular syntactic phrases. We see verb classes as the key to making generalizations about regular extensions of meaning. Current approaches to English classification, Levin classes and WordNet, have limitations in their applicability that impede their utility as general classification schemes. We present a refinement of Levin classes, intersective sets, which are a more fine-grained classification and have more coherent sets of syntactic frames and associated semantic components. We have preliminary indications that the membership of our intersective sets will be more compatible with WordNet than the original Levin classes. We also have begun to examine related classes in Portuguese, and find that these verbs demonstrate similarly coherent syntactic and semantic properties.
Page 1. Building a class-based verb lexicon using TAGs Karin Kipper, Hoa Trang Dang, William Schu... more Page 1. Building a class-based verb lexicon using TAGs Karin Kipper, Hoa Trang Dang, William Schuler, and Martha Palmer Department of Computer and Information Sciences University of Pennsylvania 200 South 33rd Street ...
In this paper we discuss a persistent problem arising from polysemy: namely the difficulty of fin... more In this paper we discuss a persistent problem arising from polysemy: namely the difficulty of finding consistent criteria for making fine-grained sense distinctions, either manually or automatically. We investigate sources of human annotator disagreements stemming from the tagging for the English Verb Lexical Sample Task in the Senseval-2 exercise in automatic Word Sense Disambiguation. We also examine errors made by a high-performing maximum entropy Word Sense Disambiguation system we developed. Both sets of errors are at least partially reconciled by a more coarse-grained view of the senses, and we present the groupings we use for quantitative coarse-grained evaluation as well as the process by which they were created. We compare the system's performance with our human annotator performance in light of both fine-grained and coarse-grained sense distinctions and show that well-defined sense groups can be of value in improving word sense disambiguation by both humans and machines.
Page 1. Martha Palmer,1 Hwee Tou Ng,2 Hoa Trang Dang3 1University of Colorado 2National Universit... more Page 1. Martha Palmer,1 Hwee Tou Ng,2 Hoa Trang Dang3 1University of Colorado 2National University of Singapore 3National Institute of Standards and Technology In this chapter we discuss the evaluation of automatic word sense disam-biguation (WSD) systems. ...
Associating semantic components with intersective Levin classes
Page 1. Associating semantic components with intersective Levin classes Hoa Trang Dang, Joseph Ro... more Page 1. Associating semantic components with intersective Levin classes Hoa Trang Dang, Joseph Rosenzweig, Martha Palmer Department of Computer and Information Science University of Pennsylvania Philadelphia PA 19104-6389 htd/josephr/[email protected] ...
We describe an automatic Word Sense Disambiguation (WSD) system that disambiguates verb senses us... more We describe an automatic Word Sense Disambiguation (WSD) system that disambiguates verb senses using syntactic and semantic features that encode information about predicate arguments and semantic classes. Our system performs at the best published accuracy on the English verbs of Senseval-2. We also experiment with using the gold-standard predicateargument labels from PropBank for disambiguating fine-grained WordNet senses and course-grained PropBank framesets, and show that disambiguation of verb senses can be further improved with better extraction of semantic roles.
Màng lọc là một lớp màng vật liệu mỏng có khả năng phân tách vật chất theo đặc tính vật lý và hóa... more Màng lọc là một lớp màng vật liệu mỏng có khả năng phân tách vật chất theo đặc tính vật lý và hóa học của chúng khi chịu một áp lực nhất định. Màng lọc ngăn cách giữa hai pha, có khả năng tạo ra sức cản để tách một số phần tử có trong nước như cặn lơ lửng, ion, vi sinh vật…khi cho dung dịch đi qua màng.
Overview of the TREC 2006 Question Answering Track
Page 1. Overview of the TREC 2006 Question Answering Track Hoa Trang Dang1, Jimmy Lin2, and Diane... more Page 1. Overview of the TREC 2006 Question Answering Track Hoa Trang Dang1, Jimmy Lin2, and Diane Kelly3 1National Institute of Standards and Technology Gaithersburg, MD 20899 [email protected] 2University of Maryland College Park, MD 20742 [email protected] ...
In this paper we present a maximum entropy Word Sense Disambiguation system we developed which pe... more In this paper we present a maximum entropy Word Sense Disambiguation system we developed which performs competitively on SENSEVAL-2 test data for English verbs. We demonstrate that using richer linguistic contextual features significantly improves tagging accuracy, and compare the system's performance with human annotator performance in light of both fine-grained and coarse-grained sense distinctions made by the sense inventory.
We present a class-based approach to building a verb lexicon that makes explicit the close associ... more We present a class-based approach to building a verb lexicon that makes explicit the close association between syntax and semantics for Levin classes. We have used Lexicalized Tree Adjoining Grammars to capture the syntax associated with each verb class and have augmented the trees to include selectional restrictions. In addition, semantic predicates are associated with each tree, which allow for a compositional interpretation.
Page 1. Sense Tagging the Penn Treebank Martha Palmer, Hoa Trang Dang, Joseph Rosenzweig Universi... more Page 1. Sense Tagging the Penn Treebank Martha Palmer, Hoa Trang Dang, Joseph Rosenzweig University of Pennsylvania 200 South 33rd Street, Philadelphia, PA, USA fmpalmer, htd, [email protected] Abstract ...
This paper describes an hierarchical approach to WordNet sense distinctions that provides differe... more This paper describes an hierarchical approach to WordNet sense distinctions that provides different types of automatic Word Sense Disambiguation (WSD) systems, which perform at varying levels of accuracy. For tasks where fine-grained sense distinctions may not be essential, an accurate coarse-grained WSD system may be sufficient. The paper discusses the criteria behind the three different levels of sense granularity, as well as the machine learning approach used by the WSD system.
We present an approach to building a verb lexicon compatible with WordNet but with explicitly sta... more We present an approach to building a verb lexicon compatible with WordNet but with explicitly stated syntactic and semantic information, using Levin verb classes to systematically construct lexical entries. By using verb classes we capture generalizations about verb behavior and reduce the effort needed to construct the lexicon. The syntactic frames for the verb classes are represented by a Lexicalized Tree Adjoining Grammar augmented with semantic predicates, which allows a compositional interpretation.
Investigations into the Role of Lexical Semantics in Word Sense Disambiguation
Verbs that can have more than one meaning pose problems for Natural Language Processing (NLP) app... more Verbs that can have more than one meaning pose problems for Natural Language Processing (NLP) applications. While homonyms (words with unrelated meanings) are fairly tractable, polysemous verbs with similar related meanings pose the greatest hurdle for automatic Word ...
In this paper we report on our experiments on automatic Word Sense Disambiguation using a maximum... more In this paper we report on our experiments on automatic Word Sense Disambiguation using a maximum entropy approach for both English and Chinese verbs. We compare the difficulty of the sensetagging tasks in the two languages and investigate the types of contextual features that are useful for each language. Our experimental results suggest that while richer linguistic features are useful for English WSD, they may not be as beneficial for Chinese.
In this paper we specifically address questions of polysemy with respect to verbs, and how regula... more In this paper we specifically address questions of polysemy with respect to verbs, and how regular extensions of meaning can be achieved through the adjunction of particular syntactic phrases. We see verb classes as the key to making generalizations about regular extensions of meaning. Current approaches to English classification, Levin classes and WordNet, have limitations in their applicability that impede their utility as general classification schemes. We present a refinement of Levin classes, intersective sets, which are a more fine-grained classification and have more coherent sets of syntactic frames and associated semantic components. We have preliminary indications that the membership of our intersective sets will be more compatible with WordNet than the original Levin classes. We also have begun to examine related classes in Portuguese, and find that these verbs demonstrate similarly coherent syntactic and semantic properties.
Page 1. Building a class-based verb lexicon using TAGs Karin Kipper, Hoa Trang Dang, William Schu... more Page 1. Building a class-based verb lexicon using TAGs Karin Kipper, Hoa Trang Dang, William Schuler, and Martha Palmer Department of Computer and Information Sciences University of Pennsylvania 200 South 33rd Street ...
In this paper we discuss a persistent problem arising from polysemy: namely the difficulty of fin... more In this paper we discuss a persistent problem arising from polysemy: namely the difficulty of finding consistent criteria for making fine-grained sense distinctions, either manually or automatically. We investigate sources of human annotator disagreements stemming from the tagging for the English Verb Lexical Sample Task in the Senseval-2 exercise in automatic Word Sense Disambiguation. We also examine errors made by a high-performing maximum entropy Word Sense Disambiguation system we developed. Both sets of errors are at least partially reconciled by a more coarse-grained view of the senses, and we present the groupings we use for quantitative coarse-grained evaluation as well as the process by which they were created. We compare the system's performance with our human annotator performance in light of both fine-grained and coarse-grained sense distinctions and show that well-defined sense groups can be of value in improving word sense disambiguation by both humans and machines.
Page 1. Martha Palmer,1 Hwee Tou Ng,2 Hoa Trang Dang3 1University of Colorado 2National Universit... more Page 1. Martha Palmer,1 Hwee Tou Ng,2 Hoa Trang Dang3 1University of Colorado 2National University of Singapore 3National Institute of Standards and Technology In this chapter we discuss the evaluation of automatic word sense disam-biguation (WSD) systems. ...
Associating semantic components with intersective Levin classes
Page 1. Associating semantic components with intersective Levin classes Hoa Trang Dang, Joseph Ro... more Page 1. Associating semantic components with intersective Levin classes Hoa Trang Dang, Joseph Rosenzweig, Martha Palmer Department of Computer and Information Science University of Pennsylvania Philadelphia PA 19104-6389 htd/josephr/[email protected] ...
We describe an automatic Word Sense Disambiguation (WSD) system that disambiguates verb senses us... more We describe an automatic Word Sense Disambiguation (WSD) system that disambiguates verb senses using syntactic and semantic features that encode information about predicate arguments and semantic classes. Our system performs at the best published accuracy on the English verbs of Senseval-2. We also experiment with using the gold-standard predicateargument labels from PropBank for disambiguating fine-grained WordNet senses and course-grained PropBank framesets, and show that disambiguation of verb senses can be further improved with better extraction of semantic roles.
Màng lọc là một lớp màng vật liệu mỏng có khả năng phân tách vật chất theo đặc tính vật lý và hóa... more Màng lọc là một lớp màng vật liệu mỏng có khả năng phân tách vật chất theo đặc tính vật lý và hóa học của chúng khi chịu một áp lực nhất định. Màng lọc ngăn cách giữa hai pha, có khả năng tạo ra sức cản để tách một số phần tử có trong nước như cặn lơ lửng, ion, vi sinh vật…khi cho dung dịch đi qua màng.
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