A Monolingual Tree-based Translation Model for Sentence Simplification

What it is about

The paper treats sentence simplification as translation from complex to simple sentences, with the complex parse tree as the source. Its Tree-based Simplification Model (TSM) covers four operations in one model: splitting, dropping, reordering and substitution. Each operation is driven by a learned feature table over tree nodes, such as a node's constituent label and its children, and the probabilities of all operation sequences that yield the same output are summed. To train it, the authors build PWKP, a parallel corpus of Wikipedia and Simple Wikipedia sentences, by aligning article pairs at sentence level with TF-IDF similarity. Evaluation uses BLEU, NIST and a readability formula; the model scores better on readability than the baseline systems. The work is the reference point for later tree-based simplifiers in this group of papers.

Ideas

• I1. Operations as counted tables. Write the four operations as counted tables keyed by UD relation and head POS, for example how often a relative clause is dropped when one Bible translation is read into the meta-world and another is produced. This keeps the model transparent and deterministic. Where: tools/translate (reader and encoder) and tools/roundtrip.
• I2. Alignment fallback. When a corpus has no verse numbering, align sentences by TF-IDF similarity before counting. Mova's current Bible pairs are verse-aligned, so this is a fallback for texts such as the school and story corpora.
• I3. Split decision as a tree-feature table. Decide split points from node features, then complete the copied material. Use the split table as the reader's check on split sentences in the meta-world.

For Mova

The dropping and reordering tables are the counted form of the operations the translator needs when an author removes or moves material. The split-and-complete step fits tools/roundtrip and the encoder's chunking (open problem 3). The model itself is not for Mova; the counted tables and the verse-free alignment fallback are.

Topics: Machine translation

Cite

The paper itself, not this card. BibTeX from the library's record of the work.

@inproceedings{zhu2010monolingual,
  title = {{A Monolingual Tree-based Translation Model for Sentence Simplification}},
  author = {Zhu, Zhemin and Bernhard, Delphine and Gurevych, Iryna},
  booktitle = {Proceedings of the 23rd International Conference on Computational Linguistics (Coling 2010)},
  year = {2010},
  url = {https://aclanthology.org/C10-1152/}
}

References

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