Heinzerling, Benjamin ; Strube, Michael ; Lin, Chin-Yew (2017)
Trust, but verify! Better entity linking through automatic verification.
Konferenzveröffentlichung, Bibliographie
Kurzbeschreibung (Abstract)
We introduce automatic verification as a post-processing step for entity linking (EL). The proposed method \emph{trusts} EL system results collectively, by assuming entity mentions are mostly linked correctly, in order to create a semantic profile of the given text using geospatial and temporal information, as well as fine-grained entity types. This profile is then used to automatically \emph{verify} each linked mention individually, i.e., to predict whether it has been linked correctly or not. Verification allows leveraging a rich set of global and pairwise features that would be prohibitively expensive for EL systems employing global inference. Evaluation shows consistent improvements across datasets and systems. In particular, when applied to state-of-the-art systems, our method yields an absolute improvement in linking performance of up to 1.7\,$F1$ on AIDA/CoNLL'03 and up to 2.4\,$F1$ on the English TAC KBP 2015 TEDL dataset.
| Typ des Eintrags: | Konferenzveröffentlichung |
|---|---|
| Erschienen: | 2017 |
| Autor(en): | Heinzerling, Benjamin ; Strube, Michael ; Lin, Chin-Yew |
| Art des Eintrags: | Bibliographie |
| Titel: | Trust, but verify! Better entity linking through automatic verification |
| Sprache: | Deutsch |
| Publikationsjahr: | 2017 |
| Buchtitel: | Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics, Valencia, Spain, 3--7 April 2017 |
| URL / URN: | http://aclweb.org/anthology/E17-1078 |
| Zugehörige Links: | |
| Kurzbeschreibung (Abstract): | We introduce automatic verification as a post-processing step for entity linking (EL). The proposed method \emph{trusts} EL system results collectively, by assuming entity mentions are mostly linked correctly, in order to create a semantic profile of the given text using geospatial and temporal information, as well as fine-grained entity types. This profile is then used to automatically \emph{verify} each linked mention individually, i.e., to predict whether it has been linked correctly or not. Verification allows leveraging a rich set of global and pairwise features that would be prohibitively expensive for EL systems employing global inference. Evaluation shows consistent improvements across datasets and systems. In particular, when applied to state-of-the-art systems, our method yields an absolute improvement in linking performance of up to 1.7\,$F1$ on AIDA/CoNLL'03 and up to 2.4\,$F1$ on the English TAC KBP 2015 TEDL dataset. |
| Freie Schlagworte: | Entity Linking;AIPHES_area_a1 |
| ID-Nummer: | TUD-CS-2017-0179 |
| Fachbereich(e)/-gebiet(e): | DFG-Graduiertenkollegs DFG-Graduiertenkollegs > Graduiertenkolleg 1994 Adaptive Informationsaufbereitung aus heterogenen Quellen |
| Hinterlegungsdatum: | 10 Jul 2017 14:02 |
| Letzte Änderung: | 28 Sep 2018 15:02 |
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