{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2019:UJZI5X5ZHARFYSWO6BOKSBJPWG","short_pith_number":"pith:UJZI5X5Z","schema_version":"1.0","canonical_sha256":"a2728edfb938225c4acef05ca9052fb182c7448ca0f8b0d53002dd15b086c43f","source":{"kind":"arxiv","id":"1906.05807","version":2},"attestation_state":"computed","paper":{"title":"Real-Time Open-Domain Question Answering with Dense-Sparse Phrase Index","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Ali Farhadi, Ankur P. Parikh, Hannaneh Hajishirzi, Jinhyuk Lee, Minjoon Seo, Tom Kwiatkowski","submitted_at":"2019-06-13T16:49:35Z","abstract_excerpt":"Existing open-domain question answering (QA) models are not suitable for real-time usage because they need to process several long documents on-demand for every input query. In this paper, we introduce the query-agnostic indexable representation of document phrases that can drastically speed up open-domain QA and also allows us to reach long-tail targets. In particular, our dense-sparse phrase encoding effectively captures syntactic, semantic, and lexical information of the phrases and eliminates the pipeline filtering of context documents. Leveraging optimization strategies, our model can be "},"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":"1906.05807","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2019-06-13T16:49:35Z","cross_cats_sorted":[],"title_canon_sha256":"c0fcba82aaae52e47e4670a85662d488ad9a7d3b82681d8ff5aca49fbac2b33a","abstract_canon_sha256":"f1881742f22eb5f651a7a590a3b165a170a4fca2257683a178ae966f03285137"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:43:22.679167Z","signature_b64":"DcaJbuu1WSulC5Z08iTYoUyemXp8nbuh41ydfLZR4dca+31iCv9g6C4hbcN96VH2i6/ZVdrMMa66DExLo/njBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"a2728edfb938225c4acef05ca9052fb182c7448ca0f8b0d53002dd15b086c43f","last_reissued_at":"2026-05-17T23:43:22.678613Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:43:22.678613Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Real-Time Open-Domain Question Answering with Dense-Sparse Phrase Index","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Ali Farhadi, Ankur P. Parikh, Hannaneh Hajishirzi, Jinhyuk Lee, Minjoon Seo, Tom Kwiatkowski","submitted_at":"2019-06-13T16:49:35Z","abstract_excerpt":"Existing open-domain question answering (QA) models are not suitable for real-time usage because they need to process several long documents on-demand for every input query. In this paper, we introduce the query-agnostic indexable representation of document phrases that can drastically speed up open-domain QA and also allows us to reach long-tail targets. In particular, our dense-sparse phrase encoding effectively captures syntactic, semantic, and lexical information of the phrases and eliminates the pipeline filtering of context documents. Leveraging optimization strategies, our model can be "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1906.05807","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":"1906.05807","created_at":"2026-05-17T23:43:22.678692+00:00"},{"alias_kind":"arxiv_version","alias_value":"1906.05807v2","created_at":"2026-05-17T23:43:22.678692+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1906.05807","created_at":"2026-05-17T23:43:22.678692+00:00"},{"alias_kind":"pith_short_12","alias_value":"UJZI5X5ZHARF","created_at":"2026-05-18T12:33:30.264802+00:00"},{"alias_kind":"pith_short_16","alias_value":"UJZI5X5ZHARFYSWO","created_at":"2026-05-18T12:33:30.264802+00:00"},{"alias_kind":"pith_short_8","alias_value":"UJZI5X5Z","created_at":"2026-05-18T12:33:30.264802+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/UJZI5X5ZHARFYSWO6BOKSBJPWG","json":"https://pith.science/pith/UJZI5X5ZHARFYSWO6BOKSBJPWG.json","graph_json":"https://pith.science/api/pith-number/UJZI5X5ZHARFYSWO6BOKSBJPWG/graph.json","events_json":"https://pith.science/api/pith-number/UJZI5X5ZHARFYSWO6BOKSBJPWG/events.json","paper":"https://pith.science/paper/UJZI5X5Z"},"agent_actions":{"view_html":"https://pith.science/pith/UJZI5X5ZHARFYSWO6BOKSBJPWG","download_json":"https://pith.science/pith/UJZI5X5ZHARFYSWO6BOKSBJPWG.json","view_paper":"https://pith.science/paper/UJZI5X5Z","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1906.05807&json=true","fetch_graph":"https://pith.science/api/pith-number/UJZI5X5ZHARFYSWO6BOKSBJPWG/graph.json","fetch_events":"https://pith.science/api/pith-number/UJZI5X5ZHARFYSWO6BOKSBJPWG/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/UJZI5X5ZHARFYSWO6BOKSBJPWG/action/timestamp_anchor","attest_storage":"https://pith.science/pith/UJZI5X5ZHARFYSWO6BOKSBJPWG/action/storage_attestation","attest_author":"https://pith.science/pith/UJZI5X5ZHARFYSWO6BOKSBJPWG/action/author_attestation","sign_citation":"https://pith.science/pith/UJZI5X5ZHARFYSWO6BOKSBJPWG/action/citation_signature","submit_replication":"https://pith.science/pith/UJZI5X5ZHARFYSWO6BOKSBJPWG/action/replication_record"}},"created_at":"2026-05-17T23:43:22.678692+00:00","updated_at":"2026-05-17T23:43:22.678692+00:00"}