{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:JIBRUOX5P7SHAZ6NSOJTJGP4RS","short_pith_number":"pith:JIBRUOX5","canonical_record":{"source":{"id":"2407.01212","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-07-01T11:58:24Z","cross_cats_sorted":[],"title_canon_sha256":"5368ed019cd7ee40f73c90965c08fe9fefb31d51ad94a83ebbb69a618c6eab56","abstract_canon_sha256":"4acb379b41e1d3e525c7ea87ba755d751bba529d1cd9de910dc8821e28e413b2"},"schema_version":"1.0"},"canonical_sha256":"4a031a3afd7fe47067cd93933499fc8c81f16251561d5f81b5a6b8d54edcb2d7","source":{"kind":"arxiv","id":"2407.01212","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2407.01212","created_at":"2026-07-05T08:38:44Z"},{"alias_kind":"arxiv_version","alias_value":"2407.01212v1","created_at":"2026-07-05T08:38:44Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2407.01212","created_at":"2026-07-05T08:38:44Z"},{"alias_kind":"pith_short_12","alias_value":"JIBRUOX5P7SH","created_at":"2026-07-05T08:38:44Z"},{"alias_kind":"pith_short_16","alias_value":"JIBRUOX5P7SHAZ6N","created_at":"2026-07-05T08:38:44Z"},{"alias_kind":"pith_short_8","alias_value":"JIBRUOX5","created_at":"2026-07-05T08:38:44Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:JIBRUOX5P7SHAZ6NSOJTJGP4RS","target":"record","payload":{"canonical_record":{"source":{"id":"2407.01212","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-07-01T11:58:24Z","cross_cats_sorted":[],"title_canon_sha256":"5368ed019cd7ee40f73c90965c08fe9fefb31d51ad94a83ebbb69a618c6eab56","abstract_canon_sha256":"4acb379b41e1d3e525c7ea87ba755d751bba529d1cd9de910dc8821e28e413b2"},"schema_version":"1.0"},"canonical_sha256":"4a031a3afd7fe47067cd93933499fc8c81f16251561d5f81b5a6b8d54edcb2d7","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:38:44.587033Z","signature_b64":"ipM87Tu2TDtpEQtnZlerL7M49CoZemSurbqE/I9e3+Z2lTOKevIcAIxLRy5i6Y4lSvYGQJ2nzVDQM8ZS/3z2CQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"4a031a3afd7fe47067cd93933499fc8c81f16251561d5f81b5a6b8d54edcb2d7","last_reissued_at":"2026-07-05T08:38:44.586605Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:38:44.586605Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2407.01212","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":"2026-07-05T08:38:44Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"AAH8dqkg4ue7QSrOWZk2VSK6h5MQj2v+lRegUhGD5GkgaUG+rd5KORGkc2pccME0EX/4/MR74eaLtyev0s3hCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T14:32:39.503008Z"},"content_sha256":"b14cf9721066033c0324519c7377dc47a4c65ff89547844317b58b32199b1781","schema_version":"1.0","event_id":"sha256:b14cf9721066033c0324519c7377dc47a4c65ff89547844317b58b32199b1781"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:JIBRUOX5P7SHAZ6NSOJTJGP4RS","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"EconNLI: Evaluating Large Language Models on Economics Reasoning","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Yi Yang, Yue Guo","submitted_at":"2024-07-01T11:58:24Z","abstract_excerpt":"Large Language Models (LLMs) are widely used for writing economic analysis reports or providing financial advice, but their ability to understand economic knowledge and reason about potential results of specific economic events lacks systematic evaluation. To address this gap, we propose a new dataset, natural language inference on economic events (EconNLI), to evaluate LLMs' knowledge and reasoning abilities in the economic domain. We evaluate LLMs on (1) their ability to correctly classify whether a premise event will cause a hypothesis event and (2) their ability to generate reasonable even"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2407.01212","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2407.01212/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":"2026-07-05T08:38:44Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"UOFogwlg5cSYryoOKWuLuF4eMkpWuoge0Xsne+gSl1nFQ6EDL2K2QzKWfcp1SIIHK/frzQrS5OxQ3eXnCSeuAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T14:32:39.504075Z"},"content_sha256":"1f77f37779affb83249e6a3c9a71e8a56a15d0b1acbf06790ebb30cf15393609","schema_version":"1.0","event_id":"sha256:1f77f37779affb83249e6a3c9a71e8a56a15d0b1acbf06790ebb30cf15393609"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/JIBRUOX5P7SHAZ6NSOJTJGP4RS/bundle.json","state_url":"https://pith.science/pith/JIBRUOX5P7SHAZ6NSOJTJGP4RS/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/JIBRUOX5P7SHAZ6NSOJTJGP4RS/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":"2026-08-09T14:32:39Z","links":{"resolver":"https://pith.science/pith/JIBRUOX5P7SHAZ6NSOJTJGP4RS","bundle":"https://pith.science/pith/JIBRUOX5P7SHAZ6NSOJTJGP4RS/bundle.json","state":"https://pith.science/pith/JIBRUOX5P7SHAZ6NSOJTJGP4RS/state.json","well_known_bundle":"https://pith.science/.well-known/pith/JIBRUOX5P7SHAZ6NSOJTJGP4RS/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:JIBRUOX5P7SHAZ6NSOJTJGP4RS","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":"4acb379b41e1d3e525c7ea87ba755d751bba529d1cd9de910dc8821e28e413b2","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-07-01T11:58:24Z","title_canon_sha256":"5368ed019cd7ee40f73c90965c08fe9fefb31d51ad94a83ebbb69a618c6eab56"},"schema_version":"1.0","source":{"id":"2407.01212","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2407.01212","created_at":"2026-07-05T08:38:44Z"},{"alias_kind":"arxiv_version","alias_value":"2407.01212v1","created_at":"2026-07-05T08:38:44Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2407.01212","created_at":"2026-07-05T08:38:44Z"},{"alias_kind":"pith_short_12","alias_value":"JIBRUOX5P7SH","created_at":"2026-07-05T08:38:44Z"},{"alias_kind":"pith_short_16","alias_value":"JIBRUOX5P7SHAZ6N","created_at":"2026-07-05T08:38:44Z"},{"alias_kind":"pith_short_8","alias_value":"JIBRUOX5","created_at":"2026-07-05T08:38:44Z"}],"graph_snapshots":[{"event_id":"sha256:1f77f37779affb83249e6a3c9a71e8a56a15d0b1acbf06790ebb30cf15393609","target":"graph","created_at":"2026-07-05T08:38:44Z","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/2407.01212/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Large Language Models (LLMs) are widely used for writing economic analysis reports or providing financial advice, but their ability to understand economic knowledge and reason about potential results of specific economic events lacks systematic evaluation. To address this gap, we propose a new dataset, natural language inference on economic events (EconNLI), to evaluate LLMs' knowledge and reasoning abilities in the economic domain. We evaluate LLMs on (1) their ability to correctly classify whether a premise event will cause a hypothesis event and (2) their ability to generate reasonable even","authors_text":"Yi Yang, Yue Guo","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-07-01T11:58:24Z","title":"EconNLI: Evaluating Large Language Models on Economics Reasoning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2407.01212","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:b14cf9721066033c0324519c7377dc47a4c65ff89547844317b58b32199b1781","target":"record","created_at":"2026-07-05T08:38:44Z","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":"4acb379b41e1d3e525c7ea87ba755d751bba529d1cd9de910dc8821e28e413b2","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-07-01T11:58:24Z","title_canon_sha256":"5368ed019cd7ee40f73c90965c08fe9fefb31d51ad94a83ebbb69a618c6eab56"},"schema_version":"1.0","source":{"id":"2407.01212","kind":"arxiv","version":1}},"canonical_sha256":"4a031a3afd7fe47067cd93933499fc8c81f16251561d5f81b5a6b8d54edcb2d7","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"4a031a3afd7fe47067cd93933499fc8c81f16251561d5f81b5a6b8d54edcb2d7","first_computed_at":"2026-07-05T08:38:44.586605Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:38:44.586605Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"ipM87Tu2TDtpEQtnZlerL7M49CoZemSurbqE/I9e3+Z2lTOKevIcAIxLRy5i6Y4lSvYGQJ2nzVDQM8ZS/3z2CQ==","signature_status":"signed_v1","signed_at":"2026-07-05T08:38:44.587033Z","signed_message":"canonical_sha256_bytes"},"source_id":"2407.01212","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:b14cf9721066033c0324519c7377dc47a4c65ff89547844317b58b32199b1781","sha256:1f77f37779affb83249e6a3c9a71e8a56a15d0b1acbf06790ebb30cf15393609"],"state_sha256":"25f38018a3830f760eed6370c298baa20b8c34cdb1e9296aabaa190c01d68b5e"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"5ZCC5aSj+ptie8Nd8gU7cyXGnPP7AdvmaUKuZf0pfKLw0/mDieNskAJwJZsqaLaukjcptaMTpjSBuEwVRfZbCg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-09T14:32:39.531684Z","bundle_sha256":"2f845c23e3633e0a3c89e896937ec22b4e743b74309512361a42c1f879c13694"}}