{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:PQ3KF3A5ZEFHHFI76NNBFSK2UW","short_pith_number":"pith:PQ3KF3A5","canonical_record":{"source":{"id":"2605.18462","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2026-05-18T14:23:35Z","cross_cats_sorted":[],"title_canon_sha256":"f780c72ea5c0934036e8a77af2864c3335c9b837cb0a0797ffd2f0882ae72057","abstract_canon_sha256":"104fa0dd5994f47619683363768209b20a05af5d3dabc03229202bfa3db8ff98"},"schema_version":"1.0"},"canonical_sha256":"7c36a2ec1dc90a73951ff35a12c95aa5b93a04bead9c3aecf2d022c1441f755d","source":{"kind":"arxiv","id":"2605.18462","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.18462","created_at":"2026-05-20T00:06:02Z"},{"alias_kind":"arxiv_version","alias_value":"2605.18462v1","created_at":"2026-05-20T00:06:02Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.18462","created_at":"2026-05-20T00:06:02Z"},{"alias_kind":"pith_short_12","alias_value":"PQ3KF3A5ZEFH","created_at":"2026-05-20T00:06:02Z"},{"alias_kind":"pith_short_16","alias_value":"PQ3KF3A5ZEFHHFI7","created_at":"2026-05-20T00:06:02Z"},{"alias_kind":"pith_short_8","alias_value":"PQ3KF3A5","created_at":"2026-05-20T00:06:02Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:PQ3KF3A5ZEFHHFI76NNBFSK2UW","target":"record","payload":{"canonical_record":{"source":{"id":"2605.18462","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2026-05-18T14:23:35Z","cross_cats_sorted":[],"title_canon_sha256":"f780c72ea5c0934036e8a77af2864c3335c9b837cb0a0797ffd2f0882ae72057","abstract_canon_sha256":"104fa0dd5994f47619683363768209b20a05af5d3dabc03229202bfa3db8ff98"},"schema_version":"1.0"},"canonical_sha256":"7c36a2ec1dc90a73951ff35a12c95aa5b93a04bead9c3aecf2d022c1441f755d","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-20T00:06:02.478984Z","signature_b64":"YnOM9181wjuf9YC8ns1QuQ8Z70cAlzPqPBLt7k4iWrwJWaH+VlW3sBAvq2umLneFC57w6GswVLUjBCwtintwBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"7c36a2ec1dc90a73951ff35a12c95aa5b93a04bead9c3aecf2d022c1441f755d","last_reissued_at":"2026-05-20T00:06:02.478131Z","signature_status":"signed_v1","first_computed_at":"2026-05-20T00:06:02.478131Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2605.18462","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":"2026-05-20T00:06:02Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"SREnwWJTwqrDT1oUKjUXhsud5J0TpzfsNymLKnyPieHjjA5D2bXO0jJRQUCrEwRbPm94d7mkDDBqVe/fXrwqDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-28T03:00:52.838066Z"},"content_sha256":"719382ba0993bc5ad3cf99b075843028be7ed7d9fdb9787edc3c877063c540f6","schema_version":"1.0","event_id":"sha256:719382ba0993bc5ad3cf99b075843028be7ed7d9fdb9787edc3c877063c540f6"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:PQ3KF3A5ZEFHHFI76NNBFSK2UW","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"From BERT to T5: A Study of Named Entity Recognition","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Mei Jia","submitted_at":"2026-05-18T14:23:35Z","abstract_excerpt":"Named entity recognition (NER) has been one of the essential preliminary steps in modern NLP applications. This report focuses on implementing the NER task on finetuning two pretrained models: (i) an encoder-only model (BERT) with a simple classification head, and (ii) a sequence-to-sequence model (T5) with few-shot prompts. Under the original 7-class tag and 3-class simplified tag schemes, BERT is applied a weighted cross-entropy for training loss, and T5 is fine-tuned with two validation strategies. It also conducted an ablation study with different hyperparameters. Moreover, the related ana"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.18462","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/2605.18462/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":"2026-05-20T00:06:02Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"+GrMum6FDwz3hEN6iel2sPscTX9gdhZqTEF3Y73avNClObM419K3cpCoae7OuhAAEOcD+fHYKEe9E57vTtkEBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-28T03:00:52.838463Z"},"content_sha256":"abbb3709fe3dd2951886e40b78a7c3aca785566215acb066cd1b00e72329693a","schema_version":"1.0","event_id":"sha256:abbb3709fe3dd2951886e40b78a7c3aca785566215acb066cd1b00e72329693a"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/PQ3KF3A5ZEFHHFI76NNBFSK2UW/bundle.json","state_url":"https://pith.science/pith/PQ3KF3A5ZEFHHFI76NNBFSK2UW/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/PQ3KF3A5ZEFHHFI76NNBFSK2UW/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":"2026-05-28T03:00:52Z","links":{"resolver":"https://pith.science/pith/PQ3KF3A5ZEFHHFI76NNBFSK2UW","bundle":"https://pith.science/pith/PQ3KF3A5ZEFHHFI76NNBFSK2UW/bundle.json","state":"https://pith.science/pith/PQ3KF3A5ZEFHHFI76NNBFSK2UW/state.json","well_known_bundle":"https://pith.science/.well-known/pith/PQ3KF3A5ZEFHHFI76NNBFSK2UW/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:PQ3KF3A5ZEFHHFI76NNBFSK2UW","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":"104fa0dd5994f47619683363768209b20a05af5d3dabc03229202bfa3db8ff98","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2026-05-18T14:23:35Z","title_canon_sha256":"f780c72ea5c0934036e8a77af2864c3335c9b837cb0a0797ffd2f0882ae72057"},"schema_version":"1.0","source":{"id":"2605.18462","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.18462","created_at":"2026-05-20T00:06:02Z"},{"alias_kind":"arxiv_version","alias_value":"2605.18462v1","created_at":"2026-05-20T00:06:02Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.18462","created_at":"2026-05-20T00:06:02Z"},{"alias_kind":"pith_short_12","alias_value":"PQ3KF3A5ZEFH","created_at":"2026-05-20T00:06:02Z"},{"alias_kind":"pith_short_16","alias_value":"PQ3KF3A5ZEFHHFI7","created_at":"2026-05-20T00:06:02Z"},{"alias_kind":"pith_short_8","alias_value":"PQ3KF3A5","created_at":"2026-05-20T00:06:02Z"}],"graph_snapshots":[{"event_id":"sha256:abbb3709fe3dd2951886e40b78a7c3aca785566215acb066cd1b00e72329693a","target":"graph","created_at":"2026-05-20T00:06:02Z","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/2605.18462/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Named entity recognition (NER) has been one of the essential preliminary steps in modern NLP applications. This report focuses on implementing the NER task on finetuning two pretrained models: (i) an encoder-only model (BERT) with a simple classification head, and (ii) a sequence-to-sequence model (T5) with few-shot prompts. Under the original 7-class tag and 3-class simplified tag schemes, BERT is applied a weighted cross-entropy for training loss, and T5 is fine-tuned with two validation strategies. It also conducted an ablation study with different hyperparameters. Moreover, the related ana","authors_text":"Mei Jia","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2026-05-18T14:23:35Z","title":"From BERT to T5: A Study of Named Entity Recognition"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.18462","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":"sha256:719382ba0993bc5ad3cf99b075843028be7ed7d9fdb9787edc3c877063c540f6","target":"record","created_at":"2026-05-20T00:06:02Z","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":"104fa0dd5994f47619683363768209b20a05af5d3dabc03229202bfa3db8ff98","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2026-05-18T14:23:35Z","title_canon_sha256":"f780c72ea5c0934036e8a77af2864c3335c9b837cb0a0797ffd2f0882ae72057"},"schema_version":"1.0","source":{"id":"2605.18462","kind":"arxiv","version":1}},"canonical_sha256":"7c36a2ec1dc90a73951ff35a12c95aa5b93a04bead9c3aecf2d022c1441f755d","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"7c36a2ec1dc90a73951ff35a12c95aa5b93a04bead9c3aecf2d022c1441f755d","first_computed_at":"2026-05-20T00:06:02.478131Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-20T00:06:02.478131Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"YnOM9181wjuf9YC8ns1QuQ8Z70cAlzPqPBLt7k4iWrwJWaH+VlW3sBAvq2umLneFC57w6GswVLUjBCwtintwBg==","signature_status":"signed_v1","signed_at":"2026-05-20T00:06:02.478984Z","signed_message":"canonical_sha256_bytes"},"source_id":"2605.18462","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:719382ba0993bc5ad3cf99b075843028be7ed7d9fdb9787edc3c877063c540f6","sha256:abbb3709fe3dd2951886e40b78a7c3aca785566215acb066cd1b00e72329693a"],"state_sha256":"77bb99ca872deedcdbe7c97b8011aa0e6313005c5fd9b07f3c9466750d230990"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"QrKt5rAa5IY1QYOVuHZunaYzJBIMTjjQTTfownC+gfjHmhOKWkkxFDJ6fGXW3Sk5aligDIK0XsBWpWXCwdWqBQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-28T03:00:52.840504Z","bundle_sha256":"992c95c53cdba28e2c043dbd392f06b18505f49098f48511cb5aaba186ec649a"}}