{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2018:664MBE4KQPF4KNEBJJFT6M53Y3","short_pith_number":"pith:664MBE4K","schema_version":"1.0","canonical_sha256":"f7b8c0938a83cbc534814a4b3f33bbc6c2a282800be248c47943d8dc7fe59e02","source":{"kind":"arxiv","id":"1804.09779","version":2},"attestation_state":"computed","paper":{"title":"On the Evaluation of Semantic Phenomena in Neural Machine Translation Using Natural Language Inference","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Adam Poliak, Benjamin Van Durme, James Glass, Yonatan Belinkov","submitted_at":"2018-04-25T20:03:09Z","abstract_excerpt":"We propose a process for investigating the extent to which sentence representations arising from neural machine translation (NMT) systems encode distinct semantic phenomena. We use these representations as features to train a natural language inference (NLI) classifier based on datasets recast from existing semantic annotations. In applying this process to a representative NMT system, we find its encoder appears most suited to supporting inferences at the syntax-semantics interface, as compared to anaphora resolution requiring world-knowledge. We conclude with a discussion on the merits and po"},"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":"1804.09779","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2018-04-25T20:03:09Z","cross_cats_sorted":[],"title_canon_sha256":"558b46222bdb7e986d005862036e43a87d663a8af5f1e77eb52e8335060244ee","abstract_canon_sha256":"1be737e5f5724aaa0f9cc4ce295c287161b113f2d59e091733374dd9ccd9cc69"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:16:41.841449Z","signature_b64":"SHHjv+OyYjmWETkFck3GfagmStUh1qAyoqrZYxIqIaMKW8X3QBvQ4W9s8EFT6rs8VdBKFZDSyEU0SgHRoxicDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"f7b8c0938a83cbc534814a4b3f33bbc6c2a282800be248c47943d8dc7fe59e02","last_reissued_at":"2026-05-18T00:16:41.840696Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:16:41.840696Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"On the Evaluation of Semantic Phenomena in Neural Machine Translation Using Natural Language Inference","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Adam Poliak, Benjamin Van Durme, James Glass, Yonatan Belinkov","submitted_at":"2018-04-25T20:03:09Z","abstract_excerpt":"We propose a process for investigating the extent to which sentence representations arising from neural machine translation (NMT) systems encode distinct semantic phenomena. We use these representations as features to train a natural language inference (NLI) classifier based on datasets recast from existing semantic annotations. In applying this process to a representative NMT system, we find its encoder appears most suited to supporting inferences at the syntax-semantics interface, as compared to anaphora resolution requiring world-knowledge. We conclude with a discussion on the merits and po"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1804.09779","kind":"arxiv","version":2},"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":"1804.09779","created_at":"2026-05-18T00:16:41.840832+00:00"},{"alias_kind":"arxiv_version","alias_value":"1804.09779v2","created_at":"2026-05-18T00:16:41.840832+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1804.09779","created_at":"2026-05-18T00:16:41.840832+00:00"},{"alias_kind":"pith_short_12","alias_value":"664MBE4KQPF4","created_at":"2026-05-18T12:32:08.215937+00:00"},{"alias_kind":"pith_short_16","alias_value":"664MBE4KQPF4KNEB","created_at":"2026-05-18T12:32:08.215937+00:00"},{"alias_kind":"pith_short_8","alias_value":"664MBE4K","created_at":"2026-05-18T12:32:08.215937+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/664MBE4KQPF4KNEBJJFT6M53Y3","json":"https://pith.science/pith/664MBE4KQPF4KNEBJJFT6M53Y3.json","graph_json":"https://pith.science/api/pith-number/664MBE4KQPF4KNEBJJFT6M53Y3/graph.json","events_json":"https://pith.science/api/pith-number/664MBE4KQPF4KNEBJJFT6M53Y3/events.json","paper":"https://pith.science/paper/664MBE4K"},"agent_actions":{"view_html":"https://pith.science/pith/664MBE4KQPF4KNEBJJFT6M53Y3","download_json":"https://pith.science/pith/664MBE4KQPF4KNEBJJFT6M53Y3.json","view_paper":"https://pith.science/paper/664MBE4K","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1804.09779&json=true","fetch_graph":"https://pith.science/api/pith-number/664MBE4KQPF4KNEBJJFT6M53Y3/graph.json","fetch_events":"https://pith.science/api/pith-number/664MBE4KQPF4KNEBJJFT6M53Y3/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/664MBE4KQPF4KNEBJJFT6M53Y3/action/timestamp_anchor","attest_storage":"https://pith.science/pith/664MBE4KQPF4KNEBJJFT6M53Y3/action/storage_attestation","attest_author":"https://pith.science/pith/664MBE4KQPF4KNEBJJFT6M53Y3/action/author_attestation","sign_citation":"https://pith.science/pith/664MBE4KQPF4KNEBJJFT6M53Y3/action/citation_signature","submit_replication":"https://pith.science/pith/664MBE4KQPF4KNEBJJFT6M53Y3/action/replication_record"}},"created_at":"2026-05-18T00:16:41.840832+00:00","updated_at":"2026-05-18T00:16:41.840832+00:00"}