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Coupled temporal scoping of relational facts

Published: 08 February 2012 Publication History

Abstract

Recent research has made significant advances in automatically constructing knowledge bases by extracting relational facts (e.g., Bill Clinton-presidentOf-US) from large text corpora. Temporally scoping such relational facts in the knowledge base (i.e., determining that Bill Clinton-presidentOf-US is true only during the period 1993 - 2001) is an important, but relatively unexplored problem. In this paper, we propose a joint inference framework for this task, which leverages fact-specific temporal constraints, and weak supervision in the form of a few labeled examples. Our proposed framework, CoTS (Coupled Temporal Scoping), exploits temporal containment, alignment, succession, and mutual exclusion constraints among facts from within and across relations. Our contribution is multi-fold. Firstly, while most previous research has focused on micro-reading approaches for temporal scoping, we pose it in a macro-reading fashion, as a change detection in a time series of facts' features computed from a large number of documents. Secondly, to the best of our knowledge, there is no other work that has used joint inference for temporal scoping. We show that joint inference is effective compared to doing temporal scoping of individual facts independently. We conduct our experiments on large scale open-domain publicly available time-stamped datasets, such as English Gigaword Corpus and Google Books Ngrams, demonstrating CoTS's effectiveness.

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      cover image ACM Conferences
      WSDM '12: Proceedings of the fifth ACM international conference on Web search and data mining
      February 2012
      792 pages
      ISBN:9781450307475
      DOI:10.1145/2124295
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      Published: 08 February 2012

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      Author Tags

      1. joint inference
      2. knowledge base
      3. temporal scoping

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      • (2024)Automatic Construction of Expiration Time Expression Dataset from RetweetsCompanion Proceedings of the ACM Web Conference 202410.1145/3589335.3651471(545-548)Online publication date: 13-May-2024
      • (2023)SocioPedia: Visualizing Social Knowledge over TimeProceedings of the 38th ACM/SIGAPP Symposium on Applied Computing10.1145/3555776.3577660(1607-1614)Online publication date: 27-Mar-2023
      • (2022)Discovering disjoint object property pairs in knowledge graphs using Probabilistic Soft LogicKnowledge and Information Systems10.1007/s10115-022-01773-765:2(899-919)Online publication date: 23-Oct-2022
      • (2020)Towards Temporal Knowledge Graph Embeddings with Arbitrary Time PrecisionProceedings of the 29th ACM International Conference on Information & Knowledge Management10.1145/3340531.3412028(685-694)Online publication date: 19-Oct-2020
      • (2020)Temporal knowledge extraction from large-scale text corpusWorld Wide Web10.1007/s11280-020-00836-524:1(135-156)Online publication date: 2-Sep-2020
      • (2020)MemTimes: Temporal Scoping of Facts with Memory NetworkDatabase Systems for Advanced Applications10.1007/978-3-030-59419-0_5(70-86)Online publication date: 22-Sep-2020
      • (2019)EventKG – the hub of event knowledge on the web – and biographical timeline generationSemantic Web10.3233/SW-19035510:6(1039-1070)Online publication date: 1-Jan-2019
      • (2019)TISCO: Temporal Scoping of FactsCompanion Proceedings of The 2019 World Wide Web Conference10.1145/3308560.3316524(959-960)Online publication date: 13-May-2019
      • (2019)Using contemporary constraints to ensure data consistencyProceedings of the 34th ACM/SIGAPP Symposium on Applied Computing10.1145/3297280.3297509(2303-2310)Online publication date: 8-Apr-2019
      • (2019)Knowledge Harvesting: Achievements and ChallengesComputing and Software Science10.1007/978-3-319-91908-9_13(217-235)Online publication date: 2019
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