{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2016:TFT2WTCSGET2D6BTST2WDSCE34","short_pith_number":"pith:TFT2WTCS","schema_version":"1.0","canonical_sha256":"9967ab4c523127a1f83394f561c844df09fca786c1d8e8e678c0875f39449288","source":{"kind":"arxiv","id":"1603.01514","version":1},"attestation_state":"computed","paper":{"title":"A Bayesian Model of Multilingual Unsupervised Semantic Role Induction","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"James Henderson, Nikhil Garg","submitted_at":"2016-03-04T16:03:53Z","abstract_excerpt":"We propose a Bayesian model of unsupervised semantic role induction in multiple languages, and use it to explore the usefulness of parallel corpora for this task. Our joint Bayesian model consists of individual models for each language plus additional latent variables that capture alignments between roles across languages. Because it is a generative Bayesian model, we can do evaluations in a variety of scenarios just by varying the inference procedure, without changing the model, thereby comparing the scenarios directly. We compare using only monolingual data, using a parallel corpus, using a "},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"1603.01514","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2016-03-04T16:03:53Z","cross_cats_sorted":[],"title_canon_sha256":"33794dd205fcec17e3b2df3a25fad58568671cc31a38f1be0487ba5d6be3bc75","abstract_canon_sha256":"54730827ea2af6d2cb9b7d8b34f1edacabc4f7f319b0817ad2855323d9049de6"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T01:19:35.810034Z","signature_b64":"sgOcAWjI9/BpwN4i9vX5PJANiBsWq8e5aXUB+VSkzKPMDbGKvrwMkREBazUpYJ+LTVhidj9fODJOBonTPSeZCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"9967ab4c523127a1f83394f561c844df09fca786c1d8e8e678c0875f39449288","last_reissued_at":"2026-05-18T01:19:35.809455Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T01:19:35.809455Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"A Bayesian Model of Multilingual Unsupervised Semantic Role Induction","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"James Henderson, Nikhil Garg","submitted_at":"2016-03-04T16:03:53Z","abstract_excerpt":"We propose a Bayesian model of unsupervised semantic role induction in multiple languages, and use it to explore the usefulness of parallel corpora for this task. Our joint Bayesian model consists of individual models for each language plus additional latent variables that capture alignments between roles across languages. Because it is a generative Bayesian model, we can do evaluations in a variety of scenarios just by varying the inference procedure, without changing the model, thereby comparing the scenarios directly. We compare using only monolingual data, using a parallel corpus, using a "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1603.01514","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"aliases":[{"alias_kind":"arxiv","alias_value":"1603.01514","created_at":"2026-05-18T01:19:35.809556+00:00"},{"alias_kind":"arxiv_version","alias_value":"1603.01514v1","created_at":"2026-05-18T01:19:35.809556+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1603.01514","created_at":"2026-05-18T01:19:35.809556+00:00"},{"alias_kind":"pith_short_12","alias_value":"TFT2WTCSGET2","created_at":"2026-05-18T12:30:44.179134+00:00"},{"alias_kind":"pith_short_16","alias_value":"TFT2WTCSGET2D6BT","created_at":"2026-05-18T12:30:44.179134+00:00"},{"alias_kind":"pith_short_8","alias_value":"TFT2WTCS","created_at":"2026-05-18T12:30:44.179134+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/TFT2WTCSGET2D6BTST2WDSCE34","json":"https://pith.science/pith/TFT2WTCSGET2D6BTST2WDSCE34.json","graph_json":"https://pith.science/api/pith-number/TFT2WTCSGET2D6BTST2WDSCE34/graph.json","events_json":"https://pith.science/api/pith-number/TFT2WTCSGET2D6BTST2WDSCE34/events.json","paper":"https://pith.science/paper/TFT2WTCS"},"agent_actions":{"view_html":"https://pith.science/pith/TFT2WTCSGET2D6BTST2WDSCE34","download_json":"https://pith.science/pith/TFT2WTCSGET2D6BTST2WDSCE34.json","view_paper":"https://pith.science/paper/TFT2WTCS","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1603.01514&json=true","fetch_graph":"https://pith.science/api/pith-number/TFT2WTCSGET2D6BTST2WDSCE34/graph.json","fetch_events":"https://pith.science/api/pith-number/TFT2WTCSGET2D6BTST2WDSCE34/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/TFT2WTCSGET2D6BTST2WDSCE34/action/timestamp_anchor","attest_storage":"https://pith.science/pith/TFT2WTCSGET2D6BTST2WDSCE34/action/storage_attestation","attest_author":"https://pith.science/pith/TFT2WTCSGET2D6BTST2WDSCE34/action/author_attestation","sign_citation":"https://pith.science/pith/TFT2WTCSGET2D6BTST2WDSCE34/action/citation_signature","submit_replication":"https://pith.science/pith/TFT2WTCSGET2D6BTST2WDSCE34/action/replication_record"}},"created_at":"2026-05-18T01:19:35.809556+00:00","updated_at":"2026-05-18T01:19:35.809556+00:00"}