{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:B64MS5Y57NQELDAURTG7PHJILQ","short_pith_number":"pith:B64MS5Y5","canonical_record":{"source":{"id":"1904.10887","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2019-04-24T15:54:46Z","cross_cats_sorted":[],"title_canon_sha256":"4f6018a048c06c38b64f14f086ccf50a731be1e0c3ec31fcbc78b1349e765901","abstract_canon_sha256":"86ba1808aabc6d04000178527010d8b7dbb9b60d100fedd9003164a041cd92e3"},"schema_version":"1.0"},"canonical_sha256":"0fb8c9771dfb60458c148ccdf79d285c2dd8351b628e939974d95bc272bf7849","source":{"kind":"arxiv","id":"1904.10887","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1904.10887","created_at":"2026-05-17T23:47:49Z"},{"alias_kind":"arxiv_version","alias_value":"1904.10887v1","created_at":"2026-05-17T23:47:49Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1904.10887","created_at":"2026-05-17T23:47:49Z"},{"alias_kind":"pith_short_12","alias_value":"B64MS5Y57NQE","created_at":"2026-05-18T12:33:12Z"},{"alias_kind":"pith_short_16","alias_value":"B64MS5Y57NQELDAU","created_at":"2026-05-18T12:33:12Z"},{"alias_kind":"pith_short_8","alias_value":"B64MS5Y5","created_at":"2026-05-18T12:33:12Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:B64MS5Y57NQELDAURTG7PHJILQ","target":"record","payload":{"canonical_record":{"source":{"id":"1904.10887","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2019-04-24T15:54:46Z","cross_cats_sorted":[],"title_canon_sha256":"4f6018a048c06c38b64f14f086ccf50a731be1e0c3ec31fcbc78b1349e765901","abstract_canon_sha256":"86ba1808aabc6d04000178527010d8b7dbb9b60d100fedd9003164a041cd92e3"},"schema_version":"1.0"},"canonical_sha256":"0fb8c9771dfb60458c148ccdf79d285c2dd8351b628e939974d95bc272bf7849","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:47:49.803943Z","signature_b64":"aH9jDoi93NY1w8ikwWukMPxP+wGQwKwgQPAveVRr5gQyKW9HyFcaLwpQULJFcu2q6whhdg4pazb2td6a7DLmAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"0fb8c9771dfb60458c148ccdf79d285c2dd8351b628e939974d95bc272bf7849","last_reissued_at":"2026-05-17T23:47:49.803350Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:47:49.803350Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1904.10887","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-17T23:47:49Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"IKYkt2mssQSeWgFy0XK17QlPkISpATWQYdBlov/+sb8EhQ8irNS9ck6hYW0B2JokNEpc2TQl3I5KkBTjDg8FDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-28T12:09:46.035046Z"},"content_sha256":"41c5cde119db7213593c956d0eda451cce3c43db8f35ffd6b5b215c7ca2c4533","schema_version":"1.0","event_id":"sha256:41c5cde119db7213593c956d0eda451cce3c43db8f35ffd6b5b215c7ca2c4533"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:B64MS5Y57NQELDAURTG7PHJILQ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Listening between the Lines: Learning Personal Attributes from Conversations","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Andrew Yates, Anna Tigunova, Gerhard Weikum, Paramita Mirza","submitted_at":"2019-04-24T15:54:46Z","abstract_excerpt":"Open-domain dialogue agents must be able to converse about many topics while incorporating knowledge about the user into the conversation. In this work we address the acquisition of such knowledge, for personalization in downstream Web applications, by extracting personal attributes from conversations. This problem is more challenging than the established task of information extraction from scientific publications or Wikipedia articles, because dialogues often give merely implicit cues about the speaker. We propose methods for inferring personal attributes, such as profession, age or family st"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1904.10887","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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-17T23:47:49Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"zvzuVeLNmRHWUlSnsBrj1x2HcQAiMVa8yew3P1N0cmGKWNPua9oyX6pkoL21JEyrW9IGKiDnPAW9qnEBk8cWCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-28T12:09:46.035422Z"},"content_sha256":"cb5ba0401aecc4d5249a0e10bf1fd7286fa24ffb577b6e34e384c08632fd7afe","schema_version":"1.0","event_id":"sha256:cb5ba0401aecc4d5249a0e10bf1fd7286fa24ffb577b6e34e384c08632fd7afe"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/B64MS5Y57NQELDAURTG7PHJILQ/bundle.json","state_url":"https://pith.science/pith/B64MS5Y57NQELDAURTG7PHJILQ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/B64MS5Y57NQELDAURTG7PHJILQ/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-05-28T12:09:46Z","links":{"resolver":"https://pith.science/pith/B64MS5Y57NQELDAURTG7PHJILQ","bundle":"https://pith.science/pith/B64MS5Y57NQELDAURTG7PHJILQ/bundle.json","state":"https://pith.science/pith/B64MS5Y57NQELDAURTG7PHJILQ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/B64MS5Y57NQELDAURTG7PHJILQ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:B64MS5Y57NQELDAURTG7PHJILQ","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"86ba1808aabc6d04000178527010d8b7dbb9b60d100fedd9003164a041cd92e3","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2019-04-24T15:54:46Z","title_canon_sha256":"4f6018a048c06c38b64f14f086ccf50a731be1e0c3ec31fcbc78b1349e765901"},"schema_version":"1.0","source":{"id":"1904.10887","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1904.10887","created_at":"2026-05-17T23:47:49Z"},{"alias_kind":"arxiv_version","alias_value":"1904.10887v1","created_at":"2026-05-17T23:47:49Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1904.10887","created_at":"2026-05-17T23:47:49Z"},{"alias_kind":"pith_short_12","alias_value":"B64MS5Y57NQE","created_at":"2026-05-18T12:33:12Z"},{"alias_kind":"pith_short_16","alias_value":"B64MS5Y57NQELDAU","created_at":"2026-05-18T12:33:12Z"},{"alias_kind":"pith_short_8","alias_value":"B64MS5Y5","created_at":"2026-05-18T12:33:12Z"}],"graph_snapshots":[{"event_id":"sha256:cb5ba0401aecc4d5249a0e10bf1fd7286fa24ffb577b6e34e384c08632fd7afe","target":"graph","created_at":"2026-05-17T23:47:49Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"paper":{"abstract_excerpt":"Open-domain dialogue agents must be able to converse about many topics while incorporating knowledge about the user into the conversation. In this work we address the acquisition of such knowledge, for personalization in downstream Web applications, by extracting personal attributes from conversations. This problem is more challenging than the established task of information extraction from scientific publications or Wikipedia articles, because dialogues often give merely implicit cues about the speaker. We propose methods for inferring personal attributes, such as profession, age or family st","authors_text":"Andrew Yates, Anna Tigunova, Gerhard Weikum, Paramita Mirza","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2019-04-24T15:54:46Z","title":"Listening between the Lines: Learning Personal Attributes from Conversations"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1904.10887","kind":"arxiv","version":1},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:41c5cde119db7213593c956d0eda451cce3c43db8f35ffd6b5b215c7ca2c4533","target":"record","created_at":"2026-05-17T23:47:49Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"86ba1808aabc6d04000178527010d8b7dbb9b60d100fedd9003164a041cd92e3","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2019-04-24T15:54:46Z","title_canon_sha256":"4f6018a048c06c38b64f14f086ccf50a731be1e0c3ec31fcbc78b1349e765901"},"schema_version":"1.0","source":{"id":"1904.10887","kind":"arxiv","version":1}},"canonical_sha256":"0fb8c9771dfb60458c148ccdf79d285c2dd8351b628e939974d95bc272bf7849","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"0fb8c9771dfb60458c148ccdf79d285c2dd8351b628e939974d95bc272bf7849","first_computed_at":"2026-05-17T23:47:49.803350Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:47:49.803350Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"aH9jDoi93NY1w8ikwWukMPxP+wGQwKwgQPAveVRr5gQyKW9HyFcaLwpQULJFcu2q6whhdg4pazb2td6a7DLmAg==","signature_status":"signed_v1","signed_at":"2026-05-17T23:47:49.803943Z","signed_message":"canonical_sha256_bytes"},"source_id":"1904.10887","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:41c5cde119db7213593c956d0eda451cce3c43db8f35ffd6b5b215c7ca2c4533","sha256:cb5ba0401aecc4d5249a0e10bf1fd7286fa24ffb577b6e34e384c08632fd7afe"],"state_sha256":"61282e2103c8a211640fb45c3352fd68d68e9dbb3c2694a28f4b347b45581f9b"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"wqesAkub+/CtE1fjtZwOhcFyX3ZBiUIoJ3qc2jweYAiU1mp8BTvnWfWRUhnUjWH7G4DECwiU0UIvV7gYKii0BQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-28T12:09:46.037442Z","bundle_sha256":"e6555e5560d78fa947282cae651435c795b551c96fcdedbfbea1d5a9c9066d1e"}}