{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2018:DNDQG7KDM7JLXU3KCNQMZG6IMT","short_pith_number":"pith:DNDQG7KD","schema_version":"1.0","canonical_sha256":"1b47037d4367d2bbd36a1360cc9bc864dcf404b777dd855a74babdd46e072a08","source":{"kind":"arxiv","id":"1812.09471","version":2},"attestation_state":"computed","paper":{"title":"Joint Slot Filling and Intent Detection via Capsule Neural Networks","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Chenwei Zhang, Nan Du, Philip S. Yu, Wei Fan, Yaliang Li","submitted_at":"2018-12-22T07:49:42Z","abstract_excerpt":"Being able to recognize words as slots and detect the intent of an utterance has been a keen issue in natural language understanding. The existing works either treat slot filling and intent detection separately in a pipeline manner, or adopt joint models which sequentially label slots while summarizing the utterance-level intent without explicitly preserving the hierarchical relationship among words, slots, and intents. To exploit the semantic hierarchy for effective modeling, we propose a capsule-based neural network model which accomplishes slot filling and intent detection via a dynamic rou"},"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":"1812.09471","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2018-12-22T07:49:42Z","cross_cats_sorted":[],"title_canon_sha256":"a9a5a2c138033d644fd882ae20fe1def89b2fb3fe1574cd901cd923d3f8072be","abstract_canon_sha256":"27475ffda6e9edeae60e9da2a50af3b0048baaf51a1e6439c4071b564adf956f"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:41:17.645977Z","signature_b64":"MR/Comd8ZAgbg4RWmyBJnpRKbPkfDON65VmhthWE/UiJBs/Dbi8LH6nMYn7RviTpCbVaLfStQd/wxAv94PQNDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"1b47037d4367d2bbd36a1360cc9bc864dcf404b777dd855a74babdd46e072a08","last_reissued_at":"2026-05-17T23:41:17.645273Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:41:17.645273Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Joint Slot Filling and Intent Detection via Capsule Neural Networks","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Chenwei Zhang, Nan Du, Philip S. Yu, Wei Fan, Yaliang Li","submitted_at":"2018-12-22T07:49:42Z","abstract_excerpt":"Being able to recognize words as slots and detect the intent of an utterance has been a keen issue in natural language understanding. The existing works either treat slot filling and intent detection separately in a pipeline manner, or adopt joint models which sequentially label slots while summarizing the utterance-level intent without explicitly preserving the hierarchical relationship among words, slots, and intents. To exploit the semantic hierarchy for effective modeling, we propose a capsule-based neural network model which accomplishes slot filling and intent detection via a dynamic rou"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1812.09471","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":"1812.09471","created_at":"2026-05-17T23:41:17.645398+00:00"},{"alias_kind":"arxiv_version","alias_value":"1812.09471v2","created_at":"2026-05-17T23:41:17.645398+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1812.09471","created_at":"2026-05-17T23:41:17.645398+00:00"},{"alias_kind":"pith_short_12","alias_value":"DNDQG7KDM7JL","created_at":"2026-05-18T12:32:19.392346+00:00"},{"alias_kind":"pith_short_16","alias_value":"DNDQG7KDM7JLXU3K","created_at":"2026-05-18T12:32:19.392346+00:00"},{"alias_kind":"pith_short_8","alias_value":"DNDQG7KD","created_at":"2026-05-18T12:32:19.392346+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/DNDQG7KDM7JLXU3KCNQMZG6IMT","json":"https://pith.science/pith/DNDQG7KDM7JLXU3KCNQMZG6IMT.json","graph_json":"https://pith.science/api/pith-number/DNDQG7KDM7JLXU3KCNQMZG6IMT/graph.json","events_json":"https://pith.science/api/pith-number/DNDQG7KDM7JLXU3KCNQMZG6IMT/events.json","paper":"https://pith.science/paper/DNDQG7KD"},"agent_actions":{"view_html":"https://pith.science/pith/DNDQG7KDM7JLXU3KCNQMZG6IMT","download_json":"https://pith.science/pith/DNDQG7KDM7JLXU3KCNQMZG6IMT.json","view_paper":"https://pith.science/paper/DNDQG7KD","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1812.09471&json=true","fetch_graph":"https://pith.science/api/pith-number/DNDQG7KDM7JLXU3KCNQMZG6IMT/graph.json","fetch_events":"https://pith.science/api/pith-number/DNDQG7KDM7JLXU3KCNQMZG6IMT/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/DNDQG7KDM7JLXU3KCNQMZG6IMT/action/timestamp_anchor","attest_storage":"https://pith.science/pith/DNDQG7KDM7JLXU3KCNQMZG6IMT/action/storage_attestation","attest_author":"https://pith.science/pith/DNDQG7KDM7JLXU3KCNQMZG6IMT/action/author_attestation","sign_citation":"https://pith.science/pith/DNDQG7KDM7JLXU3KCNQMZG6IMT/action/citation_signature","submit_replication":"https://pith.science/pith/DNDQG7KDM7JLXU3KCNQMZG6IMT/action/replication_record"}},"created_at":"2026-05-17T23:41:17.645398+00:00","updated_at":"2026-05-17T23:41:17.645398+00:00"}