PivotAlign

A system participating in the TIAD 2021 shared task. PivotAlign induces a bilingual dictionary from the Apertium graph of dictionaries, using word alignments as a scoring mechanism.

Requirements

• CombAlign (or other word alignment system)

Usage

In order to run the system, you need parallel corpora and the Apertium dictionaries or other dictionaries in the same format. I have made the parallel corpora I used in the TIAD 2021 shared task available for download. The apertium dictionaries are available here.

We assume you place the parallel corpora under PivotAlign/parallel and the Apertium dictionaries under PivotAlign/Apertium. The corpora have been tokenized and lemmatized using SpaCy.

When the data is in place, run the following:

Create co-occurrence lists from the parallel corpora

python3 create_cooc_list.py parallel/lemmatized/[src]_[trg].million.parallel.[src].lem parallel/lemmatized/[src]_[trg].million.parallel.[trg].lem --out-file working/[src]_[trg].cooc

Replace [src] with code for the source language you are working with and [trg] with the target language. For example, if working with English and French, you would replace [src] with en and [trg] with fr.

Do word alignments

Follow instructions for CombAlign or other word alignment tool. You want the output to be in Pharaoh-format:

9-15 4-8 1-2 11-15 0-0 12-16 10-9 3-5 5-7 8-14 2-3 7-12
2-4 4-6 1-2 1-0 0-1 0-3 3-5 5-7
7-10 1-2 9-11 5-4 7-6 8-10 0-0 1-1 3-3 6-7 2-2 10-12 6-5
7-10 4-3 1-0 5-4 7-6 8-11 6-9 4-1 0-2 2-2 6-5
8-6 4-5 0-1 5-3 0-0 7-0 2-1 3-2 6-4
12-15 4-8 1-2 2-5 10-13 4-4 13-16 3-6 3-7 3-4 0-0 8-9 5-7 6-8 11-14 2-3 7-8 9-12
2-4 3-6 5-8 4-7 1-3 0-1 0-0 3-5

Each line represents one sentence and pair of numbers represents an aligned SRC-TRG word pair.

Save the alignments in the alignments/ folder. [Pharaoh format]

Word alignments to word lists

python3 format_pharaoh2wordlist.py alignments/[src]_[trg].alignments parallel/lemmatized/[src]_[trg].million.parallel.[src].lem parallel/lemmatized/[src]_[trg].million.parallel.[trg].lem --out-file working/[src]_[trg]_wordlist.txt

Calculate word alignment score

python3 wordlist2wordrels_new.py working/[src]_[trg]_wordlist.txt working/[src]_[trg].cooc --out-file working/[src]_[trg]_wordlist_scores.txt

Create candidate lists by pivoting through the Apertium dictionaries

python3 pivot_apertium.py

Filter and output data, calculate precision, recall and F1

python3 filter_and_calculate_scores.py en-fr

Citation

If you use or discuss PivotAlign in published research, please cite the paper:

@inproceedings{pivotalign-tiad2021,
  author    = {Steingrímsson, Steinþór  and  Loftsson, Hrafn  and  Way, Andy},
  title     = {PivotAlign: Leveraging High-Precision Word Alignments for Bilingual Dictionary Inference},
  booktitle = {Proceedings of TIAD-2021 Shared Task – Translation Inference Across Dictionaries
co-located with the 4th Language, Data and Knowledge Conference (LDK 2021)},
  month     = {September},
  year      = {2021},
  address   = {Zaragoza, Spain},
}

License

Copyright (C) 2021, Steinþór Steingrímsson

Licensed under the terms of the Apache License, version 2.0. A full copy of the license can be found in LICENSE.