Papers with small bilingual dictionary

4 papers
Low-resource Cross-lingual Event Type Detection via Distant Supervision with Minimal Effort (C18-1)

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Challenge: Currently, few or no language processing tools or resources exist for most languages . a problem is that there is not enough available training data even in resource-rich languages if the task is complex.
Approach: They propose to use a bilingual dictionary to train machine learning in a resource-poor language . they also explore adversarial training of bilingual word representations .
Outcome: The proposed approach gives similar performance in event-type detection tasks.
Improving Cross-Lingual Word Embeddings by Meeting in the Middle (D18-1)

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Challenge: Cross-lingual word embeddings are becoming increasingly important in multilingual NLP.
Approach: They propose to apply an additional transformation after initial alignment to align two disjoint monolingual vector spaces.
Outcome: The proposed approach outperforms state-of-the-art models in monolingual and cross-lingual evaluation tasks.
Neural Cross-Lingual Relation Extraction Based on Bilingual Word Embedding Mapping (D19-1)

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Challenge: Relation extraction (RE) is an important information extraction task that seeks to detect and classify semantic relationships between entities.
Approach: They propose a bilingual word embedding mapping approach for cross-lingual RE model transfer . they use a small bilingual dictionary with only 1K word pairs to embed word pairs .
Outcome: The proposed approach achieves very good performance on target and target languages . it uses bilingual word embedding mapping to transfer a source-language model .
Automatically Building a Multilingual Lexicon of False Friends With No Supervision (2020.lrec-1)

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Challenge: a method to detect false friends from cognates is developed . cognates are words in genetically related languages with a common proto-word . in some cases, cognates have diverged from the common etymon and their meanings became different from each other.
Approach: They propose an automatic method to detect false friends from a set of cognates . cognates are words in genetically related languages which derive from etymons . authors propose a measure of "falseness" of a false friends pair based on cross-lingual word embeddings based in the system .
Outcome: The proposed method can be extended to any language pair, with monolingual corpora and a bilingual dictionary.

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