{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2021:QKJTPYJR3NB6WY3EC4OCYWJDWR","short_pith_number":"pith:QKJTPYJR","canonical_record":{"source":{"id":"2112.03073","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2021-11-26T07:58:11Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"bc1ac0f8957da36ef8c1ea4fdb722f47e8b211d78a3c16b20be283e105de1473","abstract_canon_sha256":"71b082e8f1038ee0dfdd5caea8f73946699cd29d4f0ed0dd5d64df515e26e151"},"schema_version":"1.0"},"canonical_sha256":"829337e131db43eb6364171c2c5923b44344405be89775ad29a2679287c362b4","source":{"kind":"arxiv","id":"2112.03073","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2112.03073","created_at":"2026-07-05T05:52:17Z"},{"alias_kind":"arxiv_version","alias_value":"2112.03073v3","created_at":"2026-07-05T05:52:17Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2112.03073","created_at":"2026-07-05T05:52:17Z"},{"alias_kind":"pith_short_12","alias_value":"QKJTPYJR3NB6","created_at":"2026-07-05T05:52:17Z"},{"alias_kind":"pith_short_16","alias_value":"QKJTPYJR3NB6WY3E","created_at":"2026-07-05T05:52:17Z"},{"alias_kind":"pith_short_8","alias_value":"QKJTPYJR","created_at":"2026-07-05T05:52:17Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2021:QKJTPYJR3NB6WY3EC4OCYWJDWR","target":"record","payload":{"canonical_record":{"source":{"id":"2112.03073","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2021-11-26T07:58:11Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"bc1ac0f8957da36ef8c1ea4fdb722f47e8b211d78a3c16b20be283e105de1473","abstract_canon_sha256":"71b082e8f1038ee0dfdd5caea8f73946699cd29d4f0ed0dd5d64df515e26e151"},"schema_version":"1.0"},"canonical_sha256":"829337e131db43eb6364171c2c5923b44344405be89775ad29a2679287c362b4","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:52:17.785033Z","signature_b64":"Jlhlv3mPCDY503TsrskNRf4vohxhYc3iXMMyYQGY2GBhPQ+VQJHF25A4g1/R5+5Tae3hQZIq9ZhQzkdufFVCBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"829337e131db43eb6364171c2c5923b44344405be89775ad29a2679287c362b4","last_reissued_at":"2026-07-05T05:52:17.784627Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:52:17.784627Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2112.03073","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T05:52:17Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"rIw23eB0Z1XhgP9RN9n2Pg4x/R3iH2gvL8DUbyDXakYwIaAcND0PfcVQ3VNYyA9s3J/ShBJ50rRnLUTxs1COBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-20T15:49:28.404440Z"},"content_sha256":"8b992c9664c30cfa2c4b580d5bb274745e6f1b7c8738fdfda8e458004f73ef1e","schema_version":"1.0","event_id":"sha256:8b992c9664c30cfa2c4b580d5bb274745e6f1b7c8738fdfda8e458004f73ef1e"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2021:QKJTPYJR3NB6WY3EC4OCYWJDWR","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Active Learning for Event Extraction with Memory-based Loss Prediction Model","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CL","authors_text":"Guilin Qi, Shirong Shen, Zhen Li","submitted_at":"2021-11-26T07:58:11Z","abstract_excerpt":"Event extraction (EE) plays an important role in many industrial application scenarios, and high-quality EE methods require a large amount of manual annotation data to train supervised learning models. However, the cost of obtaining annotation data is very high, especially for annotation of domain events, which requires the participation of experts from corresponding domain. So we introduce active learning (AL) technology to reduce the cost of event annotation. But the existing AL methods have two main problems, which make them not well used for event extraction. Firstly, the existing pool-bas"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2112.03073","kind":"arxiv","version":3},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2112.03073/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"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":"2026-07-05T05:52:17Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"V4aUM5ybR8w2dMP8H8QTMTQz4AZ0mYgrABTgPqqsDlN/EeB8lZhrf5VLM9HJartIwDeOMmPVi3+wHpYfk4tFDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-20T15:49:28.404803Z"},"content_sha256":"2425fe0452bba188109aca2f3aa8ec65bb0ebd72139a1896603c902ef452b8e3","schema_version":"1.0","event_id":"sha256:2425fe0452bba188109aca2f3aa8ec65bb0ebd72139a1896603c902ef452b8e3"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/QKJTPYJR3NB6WY3EC4OCYWJDWR/bundle.json","state_url":"https://pith.science/pith/QKJTPYJR3NB6WY3EC4OCYWJDWR/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/QKJTPYJR3NB6WY3EC4OCYWJDWR/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":"2026-07-20T15:49:28Z","links":{"resolver":"https://pith.science/pith/QKJTPYJR3NB6WY3EC4OCYWJDWR","bundle":"https://pith.science/pith/QKJTPYJR3NB6WY3EC4OCYWJDWR/bundle.json","state":"https://pith.science/pith/QKJTPYJR3NB6WY3EC4OCYWJDWR/state.json","well_known_bundle":"https://pith.science/.well-known/pith/QKJTPYJR3NB6WY3EC4OCYWJDWR/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:QKJTPYJR3NB6WY3EC4OCYWJDWR","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":"71b082e8f1038ee0dfdd5caea8f73946699cd29d4f0ed0dd5d64df515e26e151","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2021-11-26T07:58:11Z","title_canon_sha256":"bc1ac0f8957da36ef8c1ea4fdb722f47e8b211d78a3c16b20be283e105de1473"},"schema_version":"1.0","source":{"id":"2112.03073","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2112.03073","created_at":"2026-07-05T05:52:17Z"},{"alias_kind":"arxiv_version","alias_value":"2112.03073v3","created_at":"2026-07-05T05:52:17Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2112.03073","created_at":"2026-07-05T05:52:17Z"},{"alias_kind":"pith_short_12","alias_value":"QKJTPYJR3NB6","created_at":"2026-07-05T05:52:17Z"},{"alias_kind":"pith_short_16","alias_value":"QKJTPYJR3NB6WY3E","created_at":"2026-07-05T05:52:17Z"},{"alias_kind":"pith_short_8","alias_value":"QKJTPYJR","created_at":"2026-07-05T05:52:17Z"}],"graph_snapshots":[{"event_id":"sha256:2425fe0452bba188109aca2f3aa8ec65bb0ebd72139a1896603c902ef452b8e3","target":"graph","created_at":"2026-07-05T05:52:17Z","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"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2112.03073/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Event extraction (EE) plays an important role in many industrial application scenarios, and high-quality EE methods require a large amount of manual annotation data to train supervised learning models. However, the cost of obtaining annotation data is very high, especially for annotation of domain events, which requires the participation of experts from corresponding domain. So we introduce active learning (AL) technology to reduce the cost of event annotation. But the existing AL methods have two main problems, which make them not well used for event extraction. Firstly, the existing pool-bas","authors_text":"Guilin Qi, Shirong Shen, Zhen Li","cross_cats":["cs.AI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2021-11-26T07:58:11Z","title":"Active Learning for Event Extraction with Memory-based Loss Prediction Model"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2112.03073","kind":"arxiv","version":3},"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":"sha256:8b992c9664c30cfa2c4b580d5bb274745e6f1b7c8738fdfda8e458004f73ef1e","target":"record","created_at":"2026-07-05T05:52:17Z","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":"71b082e8f1038ee0dfdd5caea8f73946699cd29d4f0ed0dd5d64df515e26e151","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2021-11-26T07:58:11Z","title_canon_sha256":"bc1ac0f8957da36ef8c1ea4fdb722f47e8b211d78a3c16b20be283e105de1473"},"schema_version":"1.0","source":{"id":"2112.03073","kind":"arxiv","version":3}},"canonical_sha256":"829337e131db43eb6364171c2c5923b44344405be89775ad29a2679287c362b4","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"829337e131db43eb6364171c2c5923b44344405be89775ad29a2679287c362b4","first_computed_at":"2026-07-05T05:52:17.784627Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:52:17.784627Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Jlhlv3mPCDY503TsrskNRf4vohxhYc3iXMMyYQGY2GBhPQ+VQJHF25A4g1/R5+5Tae3hQZIq9ZhQzkdufFVCBQ==","signature_status":"signed_v1","signed_at":"2026-07-05T05:52:17.785033Z","signed_message":"canonical_sha256_bytes"},"source_id":"2112.03073","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:8b992c9664c30cfa2c4b580d5bb274745e6f1b7c8738fdfda8e458004f73ef1e","sha256:2425fe0452bba188109aca2f3aa8ec65bb0ebd72139a1896603c902ef452b8e3"],"state_sha256":"22bcfbddb5565f8e0d6dcc205659a8830b16317e27d2172b4d9e169ff6f9b263"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"bHEW6CzEbuaEbthDYbmIijNHPdp0frETtlIWTaGq31xRnl0KJoih8YIIiojvTo5K9wrtiNGiYsQ9FkbaAUz5BA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-20T15:49:28.407134Z","bundle_sha256":"54d2b4f5e0bc1685ccc51a09873c1b7ec66be9e6ea4779ab6028b722adce265e"}}