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Concept

LiTER Algorithm

  • (1) Select from the source text the list of words s=<s1,s2,…,sN>s = <s_1, s_2, …, s_N> belonging to the annotated idiom.
  • (2) For each word sis_i, obtain its word translations in the target language using a bilingual dictionary and add them to a blocklist bi=<t1,t2,…,tM>b_i = <t_1, t_2, …, t_M> and create a candidate list of blocklists Bs=<b1,b2,…,bN>B_s = <b_1, b_2, …, b_N>
  • (3) For each word in the reference (R), search if it occurs in any of the blocklists bib_i. If so, remove corresponding blocklist bib_i from BsB_s.
  • (4) Check if the hypothesis contains any blocklisted words. If so, mark this hypothesis as having a literal translation error.
  • The final score is the percentage of translations that trigger the blocklist. Since LiTER requires source=side annotations, test data with idioms on the source side are collected, and the spans they occur are annotated.

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Updated 2023-02-17

Contributors are:

Lois Wong
Lois Wong
🏆 1

Who are from:

University of California, Berkeley
University of California, Berkeley
🏆 1

Tags

Data Science

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