{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2021:D5YUV2MGI2TV5CT3QDU7YWNBKJ","short_pith_number":"pith:D5YUV2MG","canonical_record":{"source":{"id":"2109.14927","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2021-09-30T08:54:21Z","cross_cats_sorted":[],"title_canon_sha256":"7626606582b823a22e3e51ec0b4819f7d1425cd16e63dff3dddb15dd4f178cd6","abstract_canon_sha256":"8344a38f05fb7086e811944a1f0052d4c0d4809e833d5fd0086d43e3582a3386"},"schema_version":"1.0"},"canonical_sha256":"1f714ae98646a75e8a7b80e9fc59a1525ea69457358f5fb7caefe43da1632d74","source":{"kind":"arxiv","id":"2109.14927","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2109.14927","created_at":"2026-07-05T03:50:51Z"},{"alias_kind":"arxiv_version","alias_value":"2109.14927v3","created_at":"2026-07-05T03:50:51Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2109.14927","created_at":"2026-07-05T03:50:51Z"},{"alias_kind":"pith_short_12","alias_value":"D5YUV2MGI2TV","created_at":"2026-07-05T03:50:51Z"},{"alias_kind":"pith_short_16","alias_value":"D5YUV2MGI2TV5CT3","created_at":"2026-07-05T03:50:51Z"},{"alias_kind":"pith_short_8","alias_value":"D5YUV2MG","created_at":"2026-07-05T03:50:51Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2021:D5YUV2MGI2TV5CT3QDU7YWNBKJ","target":"record","payload":{"canonical_record":{"source":{"id":"2109.14927","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2021-09-30T08:54:21Z","cross_cats_sorted":[],"title_canon_sha256":"7626606582b823a22e3e51ec0b4819f7d1425cd16e63dff3dddb15dd4f178cd6","abstract_canon_sha256":"8344a38f05fb7086e811944a1f0052d4c0d4809e833d5fd0086d43e3582a3386"},"schema_version":"1.0"},"canonical_sha256":"1f714ae98646a75e8a7b80e9fc59a1525ea69457358f5fb7caefe43da1632d74","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T03:50:51.334238Z","signature_b64":"f3vr/EvxNaxCPsfpL1lUoL5JlkUIcCH+54xNHCdeKfFaiSCsEXi7xfhh2yuclLOfVgt9Te522Y+vQd98l7tWDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"1f714ae98646a75e8a7b80e9fc59a1525ea69457358f5fb7caefe43da1632d74","last_reissued_at":"2026-07-05T03:50:51.333775Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T03:50:51.333775Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2109.14927","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":"2026-07-05T03:50:51Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Ru4yXKl+QRWU6p2VjTq90H/Swtsuzd9ojgnxm8ai1ETXRwda/c9gUe0i88734voKYO8Xfqy8/JYc2+Pm24mMDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T09:21:47.240559Z"},"content_sha256":"d1304052d38c3643867554735fb3afd40dbbbf30e9835c7f977d8c5f4892bcac","schema_version":"1.0","event_id":"sha256:d1304052d38c3643867554735fb3afd40dbbbf30e9835c7f977d8c5f4892bcac"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2021:D5YUV2MGI2TV5CT3QDU7YWNBKJ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"BERT got a Date: Introducing Transformers to Temporal Tagging","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Dennis Aumiller, Michael Gertz, Satya Almasian","submitted_at":"2021-09-30T08:54:21Z","abstract_excerpt":"Temporal expressions in text play a significant role in language understanding and correctly identifying them is fundamental to various retrieval and natural language processing systems. Previous works have slowly shifted from rule-based to neural architectures, capable of tagging expressions with higher accuracy. However, neural models can not yet distinguish between different expression types at the same level as their rule-based counterparts. In this work, we aim to identify the most suitable transformer architecture for joint temporal tagging and type classification, as well as, investigat"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2109.14927","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/2109.14927/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":"2026-07-05T03:50:51Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"OZLgAwIveBjacISZFmznRllAC6xPbnTNoJ1c9EN2/7dFnQoDPeTigdbq9ECvnNjVxtTIOmenyb3Pb+HaVLw0Ag==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T09:21:47.241061Z"},"content_sha256":"30a116b6deeb0902ffed1d9ea7e06134a71b7fe68ceeabd7f90cdb2afa0ff195","schema_version":"1.0","event_id":"sha256:30a116b6deeb0902ffed1d9ea7e06134a71b7fe68ceeabd7f90cdb2afa0ff195"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/D5YUV2MGI2TV5CT3QDU7YWNBKJ/bundle.json","state_url":"https://pith.science/pith/D5YUV2MGI2TV5CT3QDU7YWNBKJ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/D5YUV2MGI2TV5CT3QDU7YWNBKJ/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":"2026-08-04T09:21:47Z","links":{"resolver":"https://pith.science/pith/D5YUV2MGI2TV5CT3QDU7YWNBKJ","bundle":"https://pith.science/pith/D5YUV2MGI2TV5CT3QDU7YWNBKJ/bundle.json","state":"https://pith.science/pith/D5YUV2MGI2TV5CT3QDU7YWNBKJ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/D5YUV2MGI2TV5CT3QDU7YWNBKJ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:D5YUV2MGI2TV5CT3QDU7YWNBKJ","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":"8344a38f05fb7086e811944a1f0052d4c0d4809e833d5fd0086d43e3582a3386","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2021-09-30T08:54:21Z","title_canon_sha256":"7626606582b823a22e3e51ec0b4819f7d1425cd16e63dff3dddb15dd4f178cd6"},"schema_version":"1.0","source":{"id":"2109.14927","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2109.14927","created_at":"2026-07-05T03:50:51Z"},{"alias_kind":"arxiv_version","alias_value":"2109.14927v3","created_at":"2026-07-05T03:50:51Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2109.14927","created_at":"2026-07-05T03:50:51Z"},{"alias_kind":"pith_short_12","alias_value":"D5YUV2MGI2TV","created_at":"2026-07-05T03:50:51Z"},{"alias_kind":"pith_short_16","alias_value":"D5YUV2MGI2TV5CT3","created_at":"2026-07-05T03:50:51Z"},{"alias_kind":"pith_short_8","alias_value":"D5YUV2MG","created_at":"2026-07-05T03:50:51Z"}],"graph_snapshots":[{"event_id":"sha256:30a116b6deeb0902ffed1d9ea7e06134a71b7fe68ceeabd7f90cdb2afa0ff195","target":"graph","created_at":"2026-07-05T03:50:51Z","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/2109.14927/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Temporal expressions in text play a significant role in language understanding and correctly identifying them is fundamental to various retrieval and natural language processing systems. Previous works have slowly shifted from rule-based to neural architectures, capable of tagging expressions with higher accuracy. However, neural models can not yet distinguish between different expression types at the same level as their rule-based counterparts. In this work, we aim to identify the most suitable transformer architecture for joint temporal tagging and type classification, as well as, investigat","authors_text":"Dennis Aumiller, Michael Gertz, Satya Almasian","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2021-09-30T08:54:21Z","title":"BERT got a Date: Introducing Transformers to Temporal Tagging"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2109.14927","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:d1304052d38c3643867554735fb3afd40dbbbf30e9835c7f977d8c5f4892bcac","target":"record","created_at":"2026-07-05T03:50:51Z","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":"8344a38f05fb7086e811944a1f0052d4c0d4809e833d5fd0086d43e3582a3386","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2021-09-30T08:54:21Z","title_canon_sha256":"7626606582b823a22e3e51ec0b4819f7d1425cd16e63dff3dddb15dd4f178cd6"},"schema_version":"1.0","source":{"id":"2109.14927","kind":"arxiv","version":3}},"canonical_sha256":"1f714ae98646a75e8a7b80e9fc59a1525ea69457358f5fb7caefe43da1632d74","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"1f714ae98646a75e8a7b80e9fc59a1525ea69457358f5fb7caefe43da1632d74","first_computed_at":"2026-07-05T03:50:51.333775Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T03:50:51.333775Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"f3vr/EvxNaxCPsfpL1lUoL5JlkUIcCH+54xNHCdeKfFaiSCsEXi7xfhh2yuclLOfVgt9Te522Y+vQd98l7tWDQ==","signature_status":"signed_v1","signed_at":"2026-07-05T03:50:51.334238Z","signed_message":"canonical_sha256_bytes"},"source_id":"2109.14927","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:d1304052d38c3643867554735fb3afd40dbbbf30e9835c7f977d8c5f4892bcac","sha256:30a116b6deeb0902ffed1d9ea7e06134a71b7fe68ceeabd7f90cdb2afa0ff195"],"state_sha256":"eb59dd31dc05e60a522555294a1fc400c3c154cd138eb1c47de4dfcc557aee03"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"dNCHaPPlEdcv3/Dx5mOe1mxmQ3iTRTO+VEDZtVvNLBzgCgzGH8fe/bJG+KJIhacYWsbdkEpQyCLBUUQSjP7mDg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-04T09:21:47.247154Z","bundle_sha256":"74bc9a5d22854a4888aed0c4264d6b55c9cafa209e39bb0fc6b571b77fbc0f99"}}