{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,24]],"date-time":"2026-02-24T20:14:02Z","timestamp":1771964042857,"version":"3.50.1"},"reference-count":0,"publisher":"TechForum Publishing Group","issue":"1","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Bull. Comput. Data Sci."],"published-print":{"date-parts":[[2021,12,30]]},"abstract":"<jats:p>Noun compounds (NCs) such as chocolate cake or student protest are ubiquitous in natural language yet notoriously ambiguous when interpreted in isolation. Prior work paraphrases NCs into prepositional or free-form variants but largely ignores the sentential and discourse context that often determines the intended relation. We propose CaNCi, a context-aware paraphrasing framework that conditions on local context and retrieved usage exemplars to produce faithful, diverse paraphrases with calibrated confidence. CaNCi couples a context encoder with a sequence generator and fuses evidence from a dense retriever using Fusion-in-Decoder. To make outputs reliable for downstream insertion (e.g., machine translation or information extraction), we calibrate paraphrase probabilities and construct coverage-controlled top-k sets via conformal prediction. Across standard NC benchmarks augmented with sentence contexts, CaNCi improves isomorphic and non-isomorphic scores, reduces expected calibration error, and yields safer top-k outputs at target coverage. Human evaluations show higher adequacy and fluency compared to isolate-only baselines. We release code, data recipes, and analysis protocols to facilitate reproducibility.<\/jats:p>","DOI":"10.71448\/bcds2121-5","type":"journal-article","created":{"date-parts":[[2026,2,24]],"date-time":"2026-02-24T19:55:41Z","timestamp":1771962941000},"page":"44-54","source":"Crossref","is-referenced-by-count":0,"title":["Context Aware Paraphrasing of Noun Compounds for Robust Interpretation"],"prefix":"10.71448","volume":"2","author":[{"name":"Indian Institute of Technology Bombay, Mumbai","sequence":"first","affiliation":[]},{"given":"Pushpak","family":"Bhattacharyya","sequence":"first","affiliation":[]}],"member":"52394","published-online":{"date-parts":[[2021,12,30]]},"container-title":["Bulletin of Computer and Data Sciences"],"original-title":[],"deposited":{"date-parts":[[2026,2,24]],"date-time":"2026-02-24T19:55:42Z","timestamp":1771962942000},"score":1,"resource":{"primary":{"URL":"https:\/\/bcds.ch\/context-aware-paraphrasing-of-noun-compounds-for-robust-interpretation\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,12,30]]},"references-count":0,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2021,12,30]]},"published-print":{"date-parts":[[2021,12,30]]}},"URL":"https:\/\/doi.org\/10.71448\/bcds2121-5","relation":{},"ISSN":["3072-2926"],"issn-type":[{"value":"3072-2926","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,12,30]]}}}