{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:2EHFKSTWH4M4PMGBEQEVNJTQC5","short_pith_number":"pith:2EHFKSTW","canonical_record":{"source":{"id":"1908.08983","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2019-08-23T19:15:07Z","cross_cats_sorted":[],"title_canon_sha256":"2ec9c94da50b44e0f4138c5663c320c0287511f31083b2434f4de273ab244af1","abstract_canon_sha256":"648c27a8970b4ea66a9c8a0c0e788ce8fe76fde17aa62280b1cddcd75d6ce656"},"schema_version":"1.0"},"canonical_sha256":"d10e554a763f19c7b0c1240956a6701770d54ef01d394720d451dc2d9f6c2b19","source":{"kind":"arxiv","id":"1908.08983","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1908.08983","created_at":"2026-07-04T23:59:35Z"},{"alias_kind":"arxiv_version","alias_value":"1908.08983v1","created_at":"2026-07-04T23:59:35Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1908.08983","created_at":"2026-07-04T23:59:35Z"},{"alias_kind":"pith_short_12","alias_value":"2EHFKSTWH4M4","created_at":"2026-07-04T23:59:35Z"},{"alias_kind":"pith_short_16","alias_value":"2EHFKSTWH4M4PMGB","created_at":"2026-07-04T23:59:35Z"},{"alias_kind":"pith_short_8","alias_value":"2EHFKSTW","created_at":"2026-07-04T23:59:35Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:2EHFKSTWH4M4PMGBEQEVNJTQC5","target":"record","payload":{"canonical_record":{"source":{"id":"1908.08983","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2019-08-23T19:15:07Z","cross_cats_sorted":[],"title_canon_sha256":"2ec9c94da50b44e0f4138c5663c320c0287511f31083b2434f4de273ab244af1","abstract_canon_sha256":"648c27a8970b4ea66a9c8a0c0e788ce8fe76fde17aa62280b1cddcd75d6ce656"},"schema_version":"1.0"},"canonical_sha256":"d10e554a763f19c7b0c1240956a6701770d54ef01d394720d451dc2d9f6c2b19","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-04T23:59:35.475512Z","signature_b64":"bCacMs3nrM9TQFUzWJBjc/5l/Fsno9paDq5ACijXtXDQXhEE2QgiRHIRpBzEI5OX8geF4WuPF4BodJ34Nm/zAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d10e554a763f19c7b0c1240956a6701770d54ef01d394720d451dc2d9f6c2b19","last_reissued_at":"2026-07-04T23:59:35.475115Z","signature_status":"signed_v1","first_computed_at":"2026-07-04T23:59:35.475115Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1908.08983","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":"2026-07-04T23:59:35Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"SnNiD+9RTOCw5oTev+FC0DCosZdEPukA0whAYCdDLjoxRQar7iw/nu4Wk6+Noc/2gnDzGk+jhhgdAbyUvpJtDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-16T14:46:12.914732Z"},"content_sha256":"4de4a3e40860a8b2a07bb06adb5e05f0908fd9f55a24a61c22f07bb5f67e4bbb","schema_version":"1.0","event_id":"sha256:4de4a3e40860a8b2a07bb06adb5e05f0908fd9f55a24a61c22f07bb5f67e4bbb"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:2EHFKSTWH4M4PMGBEQEVNJTQC5","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"A Little Annotation does a Lot of Good: A Study in Bootstrapping Low-resource Named Entity Recognizers","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Aditi Chaudhary, Graham Neubig, Jaime G. Carbonell, Jiateng Xie, Zaid Sheikh","submitted_at":"2019-08-23T19:15:07Z","abstract_excerpt":"Most state-of-the-art models for named entity recognition (NER) rely on the availability of large amounts of labeled data, making them challenging to extend to new, lower-resourced languages. However, there are now several proposed approaches involving either cross-lingual transfer learning, which learns from other highly resourced languages, or active learning, which efficiently selects effective training data based on model predictions. This paper poses the question: given this recent progress, and limited human annotation, what is the most effective method for efficiently creating high-qual"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1908.08983","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/1908.08983/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":"2026-07-04T23:59:35Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"IxAnsi9SnAP9pMzCS/kiaS5jouiay6QBdkaGjSRSa72lLRmhHYFkYVOgTNA7s7Aw3QgZ3QjHR3VN2PidqXtQCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-16T14:46:12.915658Z"},"content_sha256":"fa5e7d0234917a26dd9d0d98ddc304295b52696be90308e1949a1fa36a29d975","schema_version":"1.0","event_id":"sha256:fa5e7d0234917a26dd9d0d98ddc304295b52696be90308e1949a1fa36a29d975"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/2EHFKSTWH4M4PMGBEQEVNJTQC5/bundle.json","state_url":"https://pith.science/pith/2EHFKSTWH4M4PMGBEQEVNJTQC5/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/2EHFKSTWH4M4PMGBEQEVNJTQC5/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":"2026-08-16T14:46:12Z","links":{"resolver":"https://pith.science/pith/2EHFKSTWH4M4PMGBEQEVNJTQC5","bundle":"https://pith.science/pith/2EHFKSTWH4M4PMGBEQEVNJTQC5/bundle.json","state":"https://pith.science/pith/2EHFKSTWH4M4PMGBEQEVNJTQC5/state.json","well_known_bundle":"https://pith.science/.well-known/pith/2EHFKSTWH4M4PMGBEQEVNJTQC5/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:2EHFKSTWH4M4PMGBEQEVNJTQC5","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":"648c27a8970b4ea66a9c8a0c0e788ce8fe76fde17aa62280b1cddcd75d6ce656","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2019-08-23T19:15:07Z","title_canon_sha256":"2ec9c94da50b44e0f4138c5663c320c0287511f31083b2434f4de273ab244af1"},"schema_version":"1.0","source":{"id":"1908.08983","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1908.08983","created_at":"2026-07-04T23:59:35Z"},{"alias_kind":"arxiv_version","alias_value":"1908.08983v1","created_at":"2026-07-04T23:59:35Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1908.08983","created_at":"2026-07-04T23:59:35Z"},{"alias_kind":"pith_short_12","alias_value":"2EHFKSTWH4M4","created_at":"2026-07-04T23:59:35Z"},{"alias_kind":"pith_short_16","alias_value":"2EHFKSTWH4M4PMGB","created_at":"2026-07-04T23:59:35Z"},{"alias_kind":"pith_short_8","alias_value":"2EHFKSTW","created_at":"2026-07-04T23:59:35Z"}],"graph_snapshots":[{"event_id":"sha256:fa5e7d0234917a26dd9d0d98ddc304295b52696be90308e1949a1fa36a29d975","target":"graph","created_at":"2026-07-04T23:59:35Z","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/1908.08983/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Most state-of-the-art models for named entity recognition (NER) rely on the availability of large amounts of labeled data, making them challenging to extend to new, lower-resourced languages. However, there are now several proposed approaches involving either cross-lingual transfer learning, which learns from other highly resourced languages, or active learning, which efficiently selects effective training data based on model predictions. This paper poses the question: given this recent progress, and limited human annotation, what is the most effective method for efficiently creating high-qual","authors_text":"Aditi Chaudhary, Graham Neubig, Jaime G. Carbonell, Jiateng Xie, Zaid Sheikh","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2019-08-23T19:15:07Z","title":"A Little Annotation does a Lot of Good: A Study in Bootstrapping Low-resource Named Entity Recognizers"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1908.08983","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":"sha256:4de4a3e40860a8b2a07bb06adb5e05f0908fd9f55a24a61c22f07bb5f67e4bbb","target":"record","created_at":"2026-07-04T23:59:35Z","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":"648c27a8970b4ea66a9c8a0c0e788ce8fe76fde17aa62280b1cddcd75d6ce656","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2019-08-23T19:15:07Z","title_canon_sha256":"2ec9c94da50b44e0f4138c5663c320c0287511f31083b2434f4de273ab244af1"},"schema_version":"1.0","source":{"id":"1908.08983","kind":"arxiv","version":1}},"canonical_sha256":"d10e554a763f19c7b0c1240956a6701770d54ef01d394720d451dc2d9f6c2b19","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"d10e554a763f19c7b0c1240956a6701770d54ef01d394720d451dc2d9f6c2b19","first_computed_at":"2026-07-04T23:59:35.475115Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-04T23:59:35.475115Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"bCacMs3nrM9TQFUzWJBjc/5l/Fsno9paDq5ACijXtXDQXhEE2QgiRHIRpBzEI5OX8geF4WuPF4BodJ34Nm/zAg==","signature_status":"signed_v1","signed_at":"2026-07-04T23:59:35.475512Z","signed_message":"canonical_sha256_bytes"},"source_id":"1908.08983","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:4de4a3e40860a8b2a07bb06adb5e05f0908fd9f55a24a61c22f07bb5f67e4bbb","sha256:fa5e7d0234917a26dd9d0d98ddc304295b52696be90308e1949a1fa36a29d975"],"state_sha256":"db8a2afb50269d3b024918bf2c869e5eba53ce55d151b314375fd12c681ca07b"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"kqZssXyXyRbSFUYG1CPH1W0F4zJnsJYnBbn1m6ZrnmbHTdb+RtAeMZT8mfPTyopS2/zq0ipAUNajQ871bwChBg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-16T14:46:12.928456Z","bundle_sha256":"84b57f4052c02931c1a93dae7841c7b9c88d95247b4f38a49105dd217e0af581"}}