PolyUCOMP in TAC 2011 entity linking and slot filling

J. Xu; Z. Liu; Qin Lu; Y.L. Liu; C. Wang

PolyUCOMP in TAC 2011 entity linking and slot filling

J. Xu, Z. Liu, Qin Lu, Y.L. Liu, C. Wang

Research output: Unpublished conference presentation (presented paper, abstract, poster) › Conference presentation (not published in journal/proceeding/book) › Academic research › peer-review

Abstract

The PolyUCOMP team participated in two TAC-KBP2011 tasks: Regular Entity Linking and Regular Slot Filling.||For the entity linking task, a three-step entity linking system is developed. Similar to some systems in KBP 2010, a list of possible candidates are first selected. Then the best candidate is identified to decide whether a link exists. In addition, a document clustering algorithm is used to group NIL queries. This system incorporates Wikipedia linking information and other textual and contextual features. Our system produces a high answer coverage and accurate linking result. However, the NIL detection system brings significant loss in the final F-score.||For the slot filling task, we developed a system which combines query expansion and pattern-based reasoning. In expanding person queries, name variants are produced using different rules. For organization acronym queries, an abbreviation extraction technique is employed. Manually collected triggers are used for extracting other slot values. Our system ranked above median among all the participating systems.

Original language	English
Publication status	Published - 14 Nov 2011

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@conference{e0458acf7dac46b1bb3a2b1527322489,

title = "PolyUCOMP in TAC 2011 entity linking and slot filling",

abstract = "The PolyUCOMP team participated in two TAC-KBP2011 tasks: Regular Entity Linking and Regular Slot Filling.||For the entity linking task, a three-step entity linking system is developed. Similar to some systems in KBP 2010, a list of possible candidates are first selected. Then the best candidate is identified to decide whether a link exists. In addition, a document clustering algorithm is used to group NIL queries. This system incorporates Wikipedia linking information and other textual and contextual features. Our system produces a high answer coverage and accurate linking result. However, the NIL detection system brings significant loss in the final F-score.||For the slot filling task, we developed a system which combines query expansion and pattern-based reasoning. In expanding person queries, name variants are produced using different rules. For organization acronym queries, an abbreviation extraction technique is employed. Manually collected triggers are used for extracting other slot values. Our system ranked above median among all the participating systems.",

author = "J. Xu and Z. Liu and Qin Lu and Y.L. Liu and C. Wang",

year = "2011",

month = nov,

day = "14",

language = "English",

}

TY - CONF

T1 - PolyUCOMP in TAC 2011 entity linking and slot filling

AU - Xu, J.

AU - Liu, Z.

AU - Lu, Qin

AU - Liu, Y.L.

AU - Wang, C.

PY - 2011/11/14

Y1 - 2011/11/14

N2 - The PolyUCOMP team participated in two TAC-KBP2011 tasks: Regular Entity Linking and Regular Slot Filling.||For the entity linking task, a three-step entity linking system is developed. Similar to some systems in KBP 2010, a list of possible candidates are first selected. Then the best candidate is identified to decide whether a link exists. In addition, a document clustering algorithm is used to group NIL queries. This system incorporates Wikipedia linking information and other textual and contextual features. Our system produces a high answer coverage and accurate linking result. However, the NIL detection system brings significant loss in the final F-score.||For the slot filling task, we developed a system which combines query expansion and pattern-based reasoning. In expanding person queries, name variants are produced using different rules. For organization acronym queries, an abbreviation extraction technique is employed. Manually collected triggers are used for extracting other slot values. Our system ranked above median among all the participating systems.

AB - The PolyUCOMP team participated in two TAC-KBP2011 tasks: Regular Entity Linking and Regular Slot Filling.||For the entity linking task, a three-step entity linking system is developed. Similar to some systems in KBP 2010, a list of possible candidates are first selected. Then the best candidate is identified to decide whether a link exists. In addition, a document clustering algorithm is used to group NIL queries. This system incorporates Wikipedia linking information and other textual and contextual features. Our system produces a high answer coverage and accurate linking result. However, the NIL detection system brings significant loss in the final F-score.||For the slot filling task, we developed a system which combines query expansion and pattern-based reasoning. In expanding person queries, name variants are produced using different rules. For organization acronym queries, an abbreviation extraction technique is employed. Manually collected triggers are used for extracting other slot values. Our system ranked above median among all the participating systems.

M3 - Conference presentation (not published in journal/proceeding/book)

ER -

PolyUCOMP in TAC 2011 entity linking and slot filling

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