{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:4JRUGZDWAXGQ4KW6MLBSH3FQ7I","short_pith_number":"pith:4JRUGZDW","canonical_record":{"source":{"id":"2407.19568","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CL","submitted_at":"2024-07-28T19:27:06Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"62211120bfbb901ccddf74f4a064cc01e38234c7744b18e745ce9986565c1e0e","abstract_canon_sha256":"6164ccb5ab8aea215c63908bd1e414ebd38087c2b75411f692e70c7ab1da5bbe"},"schema_version":"1.0"},"canonical_sha256":"e26343647605cd0e2ade62c323ecb0fa3f9776f8a1569568ec51eb8c2fc84928","source":{"kind":"arxiv","id":"2407.19568","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2407.19568","created_at":"2026-07-05T10:18:09Z"},{"alias_kind":"arxiv_version","alias_value":"2407.19568v3","created_at":"2026-07-05T10:18:09Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2407.19568","created_at":"2026-07-05T10:18:09Z"},{"alias_kind":"pith_short_12","alias_value":"4JRUGZDWAXGQ","created_at":"2026-07-05T10:18:09Z"},{"alias_kind":"pith_short_16","alias_value":"4JRUGZDWAXGQ4KW6","created_at":"2026-07-05T10:18:09Z"},{"alias_kind":"pith_short_8","alias_value":"4JRUGZDW","created_at":"2026-07-05T10:18:09Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:4JRUGZDWAXGQ4KW6MLBSH3FQ7I","target":"record","payload":{"canonical_record":{"source":{"id":"2407.19568","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CL","submitted_at":"2024-07-28T19:27:06Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"62211120bfbb901ccddf74f4a064cc01e38234c7744b18e745ce9986565c1e0e","abstract_canon_sha256":"6164ccb5ab8aea215c63908bd1e414ebd38087c2b75411f692e70c7ab1da5bbe"},"schema_version":"1.0"},"canonical_sha256":"e26343647605cd0e2ade62c323ecb0fa3f9776f8a1569568ec51eb8c2fc84928","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:18:09.441887Z","signature_b64":"CEMQWiOK0hnrdEcdFYWzogjWfUsQuS+VbjPXKQW1+gvLBsF7iKyn5UXz5zThFl7kuTKbGw2+dbfHngVsHnXhDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"e26343647605cd0e2ade62c323ecb0fa3f9776f8a1569568ec51eb8c2fc84928","last_reissued_at":"2026-07-05T10:18:09.441473Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:18:09.441473Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2407.19568","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":"2026-07-05T10:18:09Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"kyK+PykiU9bPijvtAiOX13PeQi9sSU4OxSE6XmuXNqJiOkMsSABEdu/G8S/U+ghdqRUHIrGUdlHUa96g4HaqBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-07T06:28:57.719913Z"},"content_sha256":"6299748b3e7049a96d2f38a2898b792a0192be051e0aa3a1826a9f55be146f13","schema_version":"1.0","event_id":"sha256:6299748b3e7049a96d2f38a2898b792a0192be051e0aa3a1826a9f55be146f13"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:4JRUGZDWAXGQ4KW6MLBSH3FQ7I","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Are LLMs Good Annotators for Discourse-level Event Relation Extraction?","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CL","authors_text":"Aayush Gautam, Kangda Wei, Ruihong Huang","submitted_at":"2024-07-28T19:27:06Z","abstract_excerpt":"Large Language Models (LLMs) have demonstrated proficiency in a wide array of natural language processing tasks. However, its effectiveness over discourse-level event relation extraction (ERE) tasks remains unexplored. In this paper, we assess the effectiveness of LLMs in addressing discourse-level ERE tasks characterized by lengthy documents and intricate relations encompassing coreference, temporal, causal, and subevent types. Evaluation is conducted using an commercial model, GPT-3.5, and an open-source model, LLaMA-2. Our study reveals a notable underperformance of LLMs compared to the bas"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2407.19568","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/2407.19568/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":"2026-07-05T10:18:09Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ZLH6ePNypswzd9N69mDPTuh7RxnwVt9mUqopcQXYBWkmRKjMTGDPmk7CjjI9el2VLf8E5+B+p+oONTARqqw4BQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-07T06:28:57.720366Z"},"content_sha256":"48cc10193be7dad6541cb27ff211728a71dbdd766ef936f7306d9d4944b2c3ea","schema_version":"1.0","event_id":"sha256:48cc10193be7dad6541cb27ff211728a71dbdd766ef936f7306d9d4944b2c3ea"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/4JRUGZDWAXGQ4KW6MLBSH3FQ7I/bundle.json","state_url":"https://pith.science/pith/4JRUGZDWAXGQ4KW6MLBSH3FQ7I/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/4JRUGZDWAXGQ4KW6MLBSH3FQ7I/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":"2026-07-07T06:28:57Z","links":{"resolver":"https://pith.science/pith/4JRUGZDWAXGQ4KW6MLBSH3FQ7I","bundle":"https://pith.science/pith/4JRUGZDWAXGQ4KW6MLBSH3FQ7I/bundle.json","state":"https://pith.science/pith/4JRUGZDWAXGQ4KW6MLBSH3FQ7I/state.json","well_known_bundle":"https://pith.science/.well-known/pith/4JRUGZDWAXGQ4KW6MLBSH3FQ7I/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:4JRUGZDWAXGQ4KW6MLBSH3FQ7I","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":"6164ccb5ab8aea215c63908bd1e414ebd38087c2b75411f692e70c7ab1da5bbe","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CL","submitted_at":"2024-07-28T19:27:06Z","title_canon_sha256":"62211120bfbb901ccddf74f4a064cc01e38234c7744b18e745ce9986565c1e0e"},"schema_version":"1.0","source":{"id":"2407.19568","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2407.19568","created_at":"2026-07-05T10:18:09Z"},{"alias_kind":"arxiv_version","alias_value":"2407.19568v3","created_at":"2026-07-05T10:18:09Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2407.19568","created_at":"2026-07-05T10:18:09Z"},{"alias_kind":"pith_short_12","alias_value":"4JRUGZDWAXGQ","created_at":"2026-07-05T10:18:09Z"},{"alias_kind":"pith_short_16","alias_value":"4JRUGZDWAXGQ4KW6","created_at":"2026-07-05T10:18:09Z"},{"alias_kind":"pith_short_8","alias_value":"4JRUGZDW","created_at":"2026-07-05T10:18:09Z"}],"graph_snapshots":[{"event_id":"sha256:48cc10193be7dad6541cb27ff211728a71dbdd766ef936f7306d9d4944b2c3ea","target":"graph","created_at":"2026-07-05T10:18:09Z","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/2407.19568/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Large Language Models (LLMs) have demonstrated proficiency in a wide array of natural language processing tasks. However, its effectiveness over discourse-level event relation extraction (ERE) tasks remains unexplored. In this paper, we assess the effectiveness of LLMs in addressing discourse-level ERE tasks characterized by lengthy documents and intricate relations encompassing coreference, temporal, causal, and subevent types. Evaluation is conducted using an commercial model, GPT-3.5, and an open-source model, LLaMA-2. Our study reveals a notable underperformance of LLMs compared to the bas","authors_text":"Aayush Gautam, Kangda Wei, Ruihong Huang","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CL","submitted_at":"2024-07-28T19:27:06Z","title":"Are LLMs Good Annotators for Discourse-level Event Relation Extraction?"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2407.19568","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":"sha256:6299748b3e7049a96d2f38a2898b792a0192be051e0aa3a1826a9f55be146f13","target":"record","created_at":"2026-07-05T10:18:09Z","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":"6164ccb5ab8aea215c63908bd1e414ebd38087c2b75411f692e70c7ab1da5bbe","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CL","submitted_at":"2024-07-28T19:27:06Z","title_canon_sha256":"62211120bfbb901ccddf74f4a064cc01e38234c7744b18e745ce9986565c1e0e"},"schema_version":"1.0","source":{"id":"2407.19568","kind":"arxiv","version":3}},"canonical_sha256":"e26343647605cd0e2ade62c323ecb0fa3f9776f8a1569568ec51eb8c2fc84928","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"e26343647605cd0e2ade62c323ecb0fa3f9776f8a1569568ec51eb8c2fc84928","first_computed_at":"2026-07-05T10:18:09.441473Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:18:09.441473Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"CEMQWiOK0hnrdEcdFYWzogjWfUsQuS+VbjPXKQW1+gvLBsF7iKyn5UXz5zThFl7kuTKbGw2+dbfHngVsHnXhDA==","signature_status":"signed_v1","signed_at":"2026-07-05T10:18:09.441887Z","signed_message":"canonical_sha256_bytes"},"source_id":"2407.19568","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:6299748b3e7049a96d2f38a2898b792a0192be051e0aa3a1826a9f55be146f13","sha256:48cc10193be7dad6541cb27ff211728a71dbdd766ef936f7306d9d4944b2c3ea"],"state_sha256":"68ba7471fbba124994da282fb62c990bd95498ee73cd3f44cfe349e0e49fd4d2"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"BcCcvA/7RnROjkluUuDXf2U6WVOSW0ZgzZq3w1S4iLh61ky4LhAw9rwkwUq3rPhV11VJc6fpn3GHC+cnWPgTAg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-07T06:28:57.722589Z","bundle_sha256":"a31543aed12b735ede54b130049cfada3a0e1dace9f41e1273f69e5bb6643827"}}