Papers › Adversarial Alignment of Multilingual Models for Extracting Temporal Expressions from Text

Adversarial Alignment of Multilingual Models for Extracting Temporal Expressions from Text

19 May 2020WS 2020 7arXiv:2005.09392archive 2025-07-28

Lukas Lange, Anastasiia Iurshina, Heike Adel, Jannik Strötgen

Although temporal tagging is still dominated by rule-based systems, there have been recent attempts at neural temporal taggers. However, all of them focus on monolingual settings. In this paper, we explore multilingual methods for the extraction of temporal expressions from text and investigate adversarial training for aligning embedding spaces to one common space. With this, we create a single multilingual model that can also be transferred to unseen languages and set the new state of the art in those cross-lingual transfer experiments.

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Tasks

Cross-Lingual TransferTemporal Tagging

Results from the paper archive 2025-07-28

TaskDatasetModelMetricValueRank at snapshotLeaderboardReport
Temporal Tagging Basque TimeBank Lange et al. F1 47.87 #1 of 1 Archive leaderboard report
Temporal Tagging Catalan TimeBank 1.0 Lange et al. F1 64.21 #1 of 1 Archive leaderboard report
Temporal Tagging French Timebank Lange et al. F1 62.58 #1 of 1 Archive leaderboard report
Temporal Tagging KRAUTS Lange et al. F1 66.53 #1 of 1 Archive leaderboard report
Temporal Tagging Spanish TimeBank 1.0 Lange et al. F1 79.55 #1 of 1 Archive leaderboard report
Temporal Tagging TempEval-3 Lange et al. F1 74.8 #5 of 5 Archive leaderboard report
Temporal Tagging TimeBankPT Lange et al. F1 75.47 #1 of 1 Archive leaderboard report

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Methods

BERTfastText

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