{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:OT47Y2WEXT4JBWGYLNZBVDIH2P","short_pith_number":"pith:OT47Y2WE","canonical_record":{"source":{"id":"2201.05955","kind":"arxiv","version":5},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2022-01-16T03:13:49Z","cross_cats_sorted":[],"title_canon_sha256":"900e8e0610a3d4dcc601228be1cf58c798899e8297b96be828267e232eb4e237","abstract_canon_sha256":"86514227f985170897c538adec0c3f62866dfcf2e611e5c9b22a3f031f15e44d"},"schema_version":"1.0"},"canonical_sha256":"74f9fc6ac4bcf890d8d85b721a8d07d3f64a56b1ae4fe4a7274884d28df4ee18","source":{"kind":"arxiv","id":"2201.05955","version":5},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2201.05955","created_at":"2026-07-05T05:15:58Z"},{"alias_kind":"arxiv_version","alias_value":"2201.05955v5","created_at":"2026-07-05T05:15:58Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2201.05955","created_at":"2026-07-05T05:15:58Z"},{"alias_kind":"pith_short_12","alias_value":"OT47Y2WEXT4J","created_at":"2026-07-05T05:15:58Z"},{"alias_kind":"pith_short_16","alias_value":"OT47Y2WEXT4JBWGY","created_at":"2026-07-05T05:15:58Z"},{"alias_kind":"pith_short_8","alias_value":"OT47Y2WE","created_at":"2026-07-05T05:15:58Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:OT47Y2WEXT4JBWGYLNZBVDIH2P","target":"record","payload":{"canonical_record":{"source":{"id":"2201.05955","kind":"arxiv","version":5},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2022-01-16T03:13:49Z","cross_cats_sorted":[],"title_canon_sha256":"900e8e0610a3d4dcc601228be1cf58c798899e8297b96be828267e232eb4e237","abstract_canon_sha256":"86514227f985170897c538adec0c3f62866dfcf2e611e5c9b22a3f031f15e44d"},"schema_version":"1.0"},"canonical_sha256":"74f9fc6ac4bcf890d8d85b721a8d07d3f64a56b1ae4fe4a7274884d28df4ee18","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:15:58.521971Z","signature_b64":"XuOqjFk8Nm5TKp0dI7US4Kd/mmJ8sxOZxZcEEOP01ThpiQ9iOpZqfCtyCLLj+tFw5WBC5z7wVU+aF0ND3CChDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"74f9fc6ac4bcf890d8d85b721a8d07d3f64a56b1ae4fe4a7274884d28df4ee18","last_reissued_at":"2026-07-05T05:15:58.521418Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:15:58.521418Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2201.05955","source_version":5,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T05:15:58Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"WYtfWMTYmine2gmTpzsqTHnjaJJWLouUH9+6PjjeAIQ7AqZ4BzHaZGWWk+wdMlFTJn0wFdmJ+AeXIP/tUplwBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-18T14:24:07.899995Z"},"content_sha256":"99fc87d73d578f78bdf529764dd6ab90f71e65df53d5b3105d600b0f90256cef","schema_version":"1.0","event_id":"sha256:99fc87d73d578f78bdf529764dd6ab90f71e65df53d5b3105d600b0f90256cef"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:OT47Y2WEXT4JBWGYLNZBVDIH2P","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"WANLI: Worker and AI Collaboration for Natural Language Inference Dataset Creation","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Alisa Liu, Noah A. Smith, Swabha Swayamdipta, Yejin Choi","submitted_at":"2022-01-16T03:13:49Z","abstract_excerpt":"A recurring challenge of crowdsourcing NLP datasets at scale is that human writers often rely on repetitive patterns when crafting examples, leading to a lack of linguistic diversity. We introduce a novel approach for dataset creation based on worker and AI collaboration, which brings together the generative strength of language models and the evaluative strength of humans. Starting with an existing dataset, MultiNLI for natural language inference (NLI), our approach uses dataset cartography to automatically identify examples that demonstrate challenging reasoning patterns, and instructs GPT-3"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2201.05955","kind":"arxiv","version":5},"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/2201.05955/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":"2026-07-05T05:15:58Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"XAUI1j2O9JynEX5Z1db1BvZq0p+DOP2MPcx2ARSvGXArCoYgof5bws3qyUd+EuE3uRw9+pCS0klezC13ZC35Aw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-18T14:24:07.900921Z"},"content_sha256":"a43c6d9bb3572863e529d5821295f569b6dd9b4e99f861bd94d84774d250a576","schema_version":"1.0","event_id":"sha256:a43c6d9bb3572863e529d5821295f569b6dd9b4e99f861bd94d84774d250a576"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/OT47Y2WEXT4JBWGYLNZBVDIH2P/bundle.json","state_url":"https://pith.science/pith/OT47Y2WEXT4JBWGYLNZBVDIH2P/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/OT47Y2WEXT4JBWGYLNZBVDIH2P/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":"2026-08-18T14:24:07Z","links":{"resolver":"https://pith.science/pith/OT47Y2WEXT4JBWGYLNZBVDIH2P","bundle":"https://pith.science/pith/OT47Y2WEXT4JBWGYLNZBVDIH2P/bundle.json","state":"https://pith.science/pith/OT47Y2WEXT4JBWGYLNZBVDIH2P/state.json","well_known_bundle":"https://pith.science/.well-known/pith/OT47Y2WEXT4JBWGYLNZBVDIH2P/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:OT47Y2WEXT4JBWGYLNZBVDIH2P","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":"86514227f985170897c538adec0c3f62866dfcf2e611e5c9b22a3f031f15e44d","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2022-01-16T03:13:49Z","title_canon_sha256":"900e8e0610a3d4dcc601228be1cf58c798899e8297b96be828267e232eb4e237"},"schema_version":"1.0","source":{"id":"2201.05955","kind":"arxiv","version":5}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2201.05955","created_at":"2026-07-05T05:15:58Z"},{"alias_kind":"arxiv_version","alias_value":"2201.05955v5","created_at":"2026-07-05T05:15:58Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2201.05955","created_at":"2026-07-05T05:15:58Z"},{"alias_kind":"pith_short_12","alias_value":"OT47Y2WEXT4J","created_at":"2026-07-05T05:15:58Z"},{"alias_kind":"pith_short_16","alias_value":"OT47Y2WEXT4JBWGY","created_at":"2026-07-05T05:15:58Z"},{"alias_kind":"pith_short_8","alias_value":"OT47Y2WE","created_at":"2026-07-05T05:15:58Z"}],"graph_snapshots":[{"event_id":"sha256:a43c6d9bb3572863e529d5821295f569b6dd9b4e99f861bd94d84774d250a576","target":"graph","created_at":"2026-07-05T05:15:58Z","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/2201.05955/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"A recurring challenge of crowdsourcing NLP datasets at scale is that human writers often rely on repetitive patterns when crafting examples, leading to a lack of linguistic diversity. We introduce a novel approach for dataset creation based on worker and AI collaboration, which brings together the generative strength of language models and the evaluative strength of humans. Starting with an existing dataset, MultiNLI for natural language inference (NLI), our approach uses dataset cartography to automatically identify examples that demonstrate challenging reasoning patterns, and instructs GPT-3","authors_text":"Alisa Liu, Noah A. Smith, Swabha Swayamdipta, Yejin Choi","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2022-01-16T03:13:49Z","title":"WANLI: Worker and AI Collaboration for Natural Language Inference Dataset Creation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2201.05955","kind":"arxiv","version":5},"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":"sha256:99fc87d73d578f78bdf529764dd6ab90f71e65df53d5b3105d600b0f90256cef","target":"record","created_at":"2026-07-05T05:15:58Z","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":"86514227f985170897c538adec0c3f62866dfcf2e611e5c9b22a3f031f15e44d","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2022-01-16T03:13:49Z","title_canon_sha256":"900e8e0610a3d4dcc601228be1cf58c798899e8297b96be828267e232eb4e237"},"schema_version":"1.0","source":{"id":"2201.05955","kind":"arxiv","version":5}},"canonical_sha256":"74f9fc6ac4bcf890d8d85b721a8d07d3f64a56b1ae4fe4a7274884d28df4ee18","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"74f9fc6ac4bcf890d8d85b721a8d07d3f64a56b1ae4fe4a7274884d28df4ee18","first_computed_at":"2026-07-05T05:15:58.521418Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:15:58.521418Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"XuOqjFk8Nm5TKp0dI7US4Kd/mmJ8sxOZxZcEEOP01ThpiQ9iOpZqfCtyCLLj+tFw5WBC5z7wVU+aF0ND3CChDw==","signature_status":"signed_v1","signed_at":"2026-07-05T05:15:58.521971Z","signed_message":"canonical_sha256_bytes"},"source_id":"2201.05955","source_kind":"arxiv","source_version":5}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:99fc87d73d578f78bdf529764dd6ab90f71e65df53d5b3105d600b0f90256cef","sha256:a43c6d9bb3572863e529d5821295f569b6dd9b4e99f861bd94d84774d250a576"],"state_sha256":"5a04ee9385641f62bbb5c5d6d5f2cfcabc092a25cbc8670b3482db9d6d9bf0f2"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"+Ke6tvAgY8vLd/y7g7Lr2+kkRWfgGvXIrDwe4yUF6xnoNFghvCvsugv1++f6yOwdUmeLNMMBJJx62Tgq/N7GBA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-18T14:24:07.913422Z","bundle_sha256":"76bfe14ba91a1eb882e1f7ce20a15f6d73bb0fe3c4a2735dbcb90293487766b5"}}