Constrained Sequence-to-sequence Semitic Root Extraction for Enriching Word Embeddings
What it is about
The authors extract the root of a Semitic word with a sequence-to-sequence model (a BiGRU encoder and a GRU decoder over characters). The novelty is constrained beam search: a trie built from the dictionary of valid roots prunes every decoding step, so the output is always a real root. The model is compared with multiclass classifiers, unconstrained seq2seq models and rule-based stemmers. Five-fold accuracy is 98.8% on a Hebrew word-root list of about 11,500 words (roughly 500 roots, Wiktionary-derived) and 83.2% on an Arabic list of 140K words (11K roots). On rare Arabic roots (three or fewer training occurrences) and on unseen roots the constrained model still does best. The root is then used to split words into prefix, stem and suffix slots, and these slots enrich FastText-style embeddings, which helps on morphemic analogies and word similarity.
Ideas
- I1. Trie-constrained output as a plain lookup: a candidate root is accepted only if it is in the root table, and otherwise the analyser keeps all candidates and reports the word as unknown. For Hebrew, with a few hundred roots, this is a finite-state check that costs nothing and can be explained.
- I2. Stem and slot rule: the stem is the shortest contiguous span that contains the root in order; letters outside it are prefixes and suffixes, and letters that fall inside the gaps of the root are infixes. For Hebrew, write the analogous templates from the grammar (the binyanim and the weak-verb patterns), not by copying the Arabic slots.
- I3. A test set for root extraction: split Hebrew roots by frequency (rare, unseen) and report accuracy on each group, as the paper does, before adding any learned component to
tools/hbo.
For Mova
I1 is a rule for The verb and The Noun, the Adjective and the Numeral (root check); I2 belongs in The weak verbs and The Noun, the Adjective and the Numeral; I3 is a measure for tools/hbo. The Wiktionary-derived root list is CC BY-SA data: it may be tested against and learned from, but it is not carried into a release.
Cite
@inproceedings{elkishky2019constrained,
title = {{Constrained Sequence-to-sequence Semitic Root Extraction for Enriching Word Embeddings}},
author = {El-Kishky, Ahmed and Fu, Xingyu and Addawood, Aseel and Sobh, Nahil and Voss, Clare and Han, Jiawei},
booktitle = {Proceedings of the Fourth Arabic Natural Language Processing Workshop},
year = {2019},
doi = {10.18653/v1/w19-4610},
url = {https://doi.org/10.18653/v1/w19-4610}
}References
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