Abstract
Natural languages are inherently ambiguous. Ambiguities exist at many levels, word sense ambiguity being one of them. Resolving sense ambiguity is crucial in many Natural Language Processing applications. In this paper, we focus on word sense ambiguity and propose an unsupervised graph-based algorithm for Hindi Word Sense disambiguation task. The work is motivated by the encouraging results achieved by graph-based WSD algorithms for English and other European languages and the lack of wide-coverage sense annotated dataset for Hindi. The proposed algorithm creates a weighted graph wherein the nodes represent the senses of words appearing in the context of an ambiguous word and the edges depict relations between them. It uses semantic similarity derived from Hindi WordNet to assign weight to edges and a random walk-type algorithm to assign the most appropriate sense to a polysemous word in a given context. The evaluation has been done on a sense annotated dataset comprising 20 polysemous nouns. We observed an overall accuracy of 63.39% which is better than earlier reported work on the same dataset.
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Appendix I
Appendix I
अगर | अगली | अगले | अच्छी | अति | अथवा | अधिक | अनुसार | अनेक |
अन्य | अपना | अपनी | अपने | अब | अभी | अलावा | आ | आई |
आएाँ | आगे | आती | आदि | आने | आप | आम | आसपास | इतनी |
इतने | इन | इनमे | इन्हीं | इन्हे | इस | इसका | इसकी | इसके |
लिए | इसके | इसमें | इसलिए | इससे | इसी | इसीलिए | इसे | उतनी |
उधर | उन | उनका | उनकी | उनके | उनमें | उनसे | उन्हीं | उन्हे |
उन्हें | उन्होंने | उन्होने | उस | उसका | उसकी | उसके | उससे | उसी |
उसे | ऊपर | एक | एक-एक | एवं | ऐसा | ऐसी | ऐसे | ओर |
कई | कछ | कब | कभी | कभी-कभी | कम | कया | कर | करके |
करता | करती | करते | करना | करनी | करने | करा | कराने | कराया |
करेंगे | करेगा | करेगी | का | काफी | काफी | कि | किंतु | किए |
कितनी | कितने | किन | किया | किये | किस | किसी | की | कुछ |
कुल | के | कारण | कैसे | को | कोई | कौन | क्या | क्यो |
क्योकि | गई | गईं | गए | गया | गयी | गये | चलता | चलने |
चली | चाहती | चाहते | चाहिए | चाहे | चुका | चुकी | चुके | चुके |
छह | छू | जगह | जब | जबकि | जल्द | जल्दी | जहाँ | जहां |
जहां-तहां | जा | जाए | जाएं | जाएंगी | जाएगी | जाएाँ | जाकर | जाता |
जाती | जाते | जानना | जाना | जाने | जाये | जारी | जितना | जितनी |
जिनमें | जिन्हें | जिसका | जिससे | जिसे | जी | जैसा | जैसे | जो |
जोर | ज्यादा | ठीक | तक | तथा | तब | तभी | तरफ | तरह |
तहत | ताकि | तीन | तो | तौर | था | थी | थे | थोडा |
दरअसल | दिए | दिखाए | दिया | दी | दूर | दूसरी | दूसरे | दे |
देंगी | देंगे | देकर | देता | देती | देते | देना | देने | दो |
दोनो | द्वारा | न | नई | नए | नया | नहीं | नीचे | ने |
पडता | पडने | पडा | पर | परंत | पहला | पहले | पांच | पाएं |
पााँच | पीछे | पूरी | प्रति | प्रत्येक | फिर | बजाय | बजे | बडी |
बढ़ | बढ़ा | बढ़े | बताया | बन | बनाई | बनाए | बनाना | बनाने |
बनी | बने | बल्कि | बहुत | बाकी | बाद | बार | बार-बार | बारे |
बिना | बीच | बेहद | भी | मगर | मुताबिक | मे | में | यदि |
यद्यपि | यह | यहाँ | यही | या | यानी | ये | रखना | रह |
रहती | रही | रहे | रहेगा | रहेगी | रहो | रोका | लगभग | लगा |
लगाई | लगे | लाकर | लाने | लिए | लिया | लिये | ली | ले |
लेकर | लेकिन | लेगी | लेना | लेने | व | वनाट | वह | वहााँ |
वहीं | वाला | वाली | वाले | वालो | विभिन्न | वे | वैसे | वो |
शायद | सकता | सकती | सकते | सका | सके | सकेगा | सकेगी | सब |
सबकी | सबके | सबसे | सभी | सहज | सही | सा | सात | साथ |
साथ-साथ | साफ | सामने | सारे | सिर्फ | सीधे | से | हाँ | हम |
हमने | हमारी | हमारे | हमें | हर | हां | हांलांकि | ही | हुआ |
हुई | हुए | हूँ | है | हैं | हो | हों | होंगी | होगा |
होगी | होता | होती | होते | होना | होनी | होने |
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Jha, P., Agarwal, S., Abbas, A. et al. A Novel Unsupervısed Graph-Based Algorıthm for Hindi Word Sense Disambiguation. SN COMPUT. SCI. 4, 675 (2023). https://doi.org/10.1007/s42979-023-02116-1
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DOI: https://doi.org/10.1007/s42979-023-02116-1