{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:ONPYKUMDRSO3666UJI7KP3RFKY","short_pith_number":"pith:ONPYKUMD","canonical_record":{"source":{"id":"1803.07640","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2018-03-20T20:32:07Z","cross_cats_sorted":[],"title_canon_sha256":"a9b20cb85b0782ec00b4a28cfd667452098fa790a2a30bd2fc7184e471838917","abstract_canon_sha256":"fb2c2aaf76eb5ad41aeac1cb33f8584a1a8eea622c933b4440cc38a5949f847e"},"schema_version":"1.0"},"canonical_sha256":"735f8551838c9dbf7bd44a3ea7ee255639f7db0957359795224f78594f187ce6","source":{"kind":"arxiv","id":"1803.07640","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1803.07640","created_at":"2026-05-18T00:14:33Z"},{"alias_kind":"arxiv_version","alias_value":"1803.07640v2","created_at":"2026-05-18T00:14:33Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1803.07640","created_at":"2026-05-18T00:14:33Z"},{"alias_kind":"pith_short_12","alias_value":"ONPYKUMDRSO3","created_at":"2026-05-18T12:32:43Z"},{"alias_kind":"pith_short_16","alias_value":"ONPYKUMDRSO3666U","created_at":"2026-05-18T12:32:43Z"},{"alias_kind":"pith_short_8","alias_value":"ONPYKUMD","created_at":"2026-05-18T12:32:43Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:ONPYKUMDRSO3666UJI7KP3RFKY","target":"record","payload":{"canonical_record":{"source":{"id":"1803.07640","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2018-03-20T20:32:07Z","cross_cats_sorted":[],"title_canon_sha256":"a9b20cb85b0782ec00b4a28cfd667452098fa790a2a30bd2fc7184e471838917","abstract_canon_sha256":"fb2c2aaf76eb5ad41aeac1cb33f8584a1a8eea622c933b4440cc38a5949f847e"},"schema_version":"1.0"},"canonical_sha256":"735f8551838c9dbf7bd44a3ea7ee255639f7db0957359795224f78594f187ce6","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:14:33.915897Z","signature_b64":"tjoqMnohLCbMko2gYG6Ia2rKelmpaCn0Ma9S77FbOImopXKkbwI46OsbA/K6Vd2BI69262Z/MyeFJDbepN3FDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"735f8551838c9dbf7bd44a3ea7ee255639f7db0957359795224f78594f187ce6","last_reissued_at":"2026-05-18T00:14:33.915075Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:14:33.915075Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1803.07640","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T00:14:33Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"XsQmddJDFGm7/m1LKfbXRkgtev0zkVHHrL1b8XePcMsVunlT7OGa+yRBnTc5czBPMN5HE5lA3KjKxF3wbwpLDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-20T00:02:22.543591Z"},"content_sha256":"1015aacbbae62ca0b9d3be94da56d8c385df649eb2b1aeeabeb86c7dfe7f0e4b","schema_version":"1.0","event_id":"sha256:1015aacbbae62ca0b9d3be94da56d8c385df649eb2b1aeeabeb86c7dfe7f0e4b"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:ONPYKUMDRSO3666UJI7KP3RFKY","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"AllenNLP: A Deep Semantic Natural Language Processing Platform","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Joel Grus, Luke Zettlemoyer, Mark Neumann, Matt Gardner, Matthew Peters, Michael Schmitz, Nelson Liu, Oyvind Tafjord, Pradeep Dasigi","submitted_at":"2018-03-20T20:32:07Z","abstract_excerpt":"This paper describes AllenNLP, a platform for research on deep learning methods in natural language understanding. AllenNLP is designed to support researchers who want to build novel language understanding models quickly and easily. It is built on top of PyTorch, allowing for dynamic computation graphs, and provides (1) a flexible data API that handles intelligent batching and padding, (2) high-level abstractions for common operations in working with text, and (3) a modular and extensible experiment framework that makes doing good science easy. It also includes reference implementations of hig"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1803.07640","kind":"arxiv","version":2},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"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":"2026-05-18T00:14:33Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"WiBoo0BlkXyVp7oIP+YHF5DzaTcRHRhfF2SJgn250WbPGj+iA/PbtDtxCv1ntjhvjyk6ShrB0unFMwbX1ESoDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-20T00:02:22.552937Z"},"content_sha256":"d813ca8006def13e1ff3623c00bfc24c752f69d048aaa6f0e922dc0fc4aea71e","schema_version":"1.0","event_id":"sha256:d813ca8006def13e1ff3623c00bfc24c752f69d048aaa6f0e922dc0fc4aea71e"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/ONPYKUMDRSO3666UJI7KP3RFKY/bundle.json","state_url":"https://pith.science/pith/ONPYKUMDRSO3666UJI7KP3RFKY/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/ONPYKUMDRSO3666UJI7KP3RFKY/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":"2026-08-20T00:02:22Z","links":{"resolver":"https://pith.science/pith/ONPYKUMDRSO3666UJI7KP3RFKY","bundle":"https://pith.science/pith/ONPYKUMDRSO3666UJI7KP3RFKY/bundle.json","state":"https://pith.science/pith/ONPYKUMDRSO3666UJI7KP3RFKY/state.json","well_known_bundle":"https://pith.science/.well-known/pith/ONPYKUMDRSO3666UJI7KP3RFKY/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:ONPYKUMDRSO3666UJI7KP3RFKY","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":"fb2c2aaf76eb5ad41aeac1cb33f8584a1a8eea622c933b4440cc38a5949f847e","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2018-03-20T20:32:07Z","title_canon_sha256":"a9b20cb85b0782ec00b4a28cfd667452098fa790a2a30bd2fc7184e471838917"},"schema_version":"1.0","source":{"id":"1803.07640","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1803.07640","created_at":"2026-05-18T00:14:33Z"},{"alias_kind":"arxiv_version","alias_value":"1803.07640v2","created_at":"2026-05-18T00:14:33Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1803.07640","created_at":"2026-05-18T00:14:33Z"},{"alias_kind":"pith_short_12","alias_value":"ONPYKUMDRSO3","created_at":"2026-05-18T12:32:43Z"},{"alias_kind":"pith_short_16","alias_value":"ONPYKUMDRSO3666U","created_at":"2026-05-18T12:32:43Z"},{"alias_kind":"pith_short_8","alias_value":"ONPYKUMD","created_at":"2026-05-18T12:32:43Z"}],"graph_snapshots":[{"event_id":"sha256:d813ca8006def13e1ff3623c00bfc24c752f69d048aaa6f0e922dc0fc4aea71e","target":"graph","created_at":"2026-05-18T00:14:33Z","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"},"paper":{"abstract_excerpt":"This paper describes AllenNLP, a platform for research on deep learning methods in natural language understanding. AllenNLP is designed to support researchers who want to build novel language understanding models quickly and easily. It is built on top of PyTorch, allowing for dynamic computation graphs, and provides (1) a flexible data API that handles intelligent batching and padding, (2) high-level abstractions for common operations in working with text, and (3) a modular and extensible experiment framework that makes doing good science easy. It also includes reference implementations of hig","authors_text":"Joel Grus, Luke Zettlemoyer, Mark Neumann, Matt Gardner, Matthew Peters, Michael Schmitz, Nelson Liu, Oyvind Tafjord, Pradeep Dasigi","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2018-03-20T20:32:07Z","title":"AllenNLP: A Deep Semantic Natural Language Processing Platform"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1803.07640","kind":"arxiv","version":2},"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":"sha256:1015aacbbae62ca0b9d3be94da56d8c385df649eb2b1aeeabeb86c7dfe7f0e4b","target":"record","created_at":"2026-05-18T00:14:33Z","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":"fb2c2aaf76eb5ad41aeac1cb33f8584a1a8eea622c933b4440cc38a5949f847e","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2018-03-20T20:32:07Z","title_canon_sha256":"a9b20cb85b0782ec00b4a28cfd667452098fa790a2a30bd2fc7184e471838917"},"schema_version":"1.0","source":{"id":"1803.07640","kind":"arxiv","version":2}},"canonical_sha256":"735f8551838c9dbf7bd44a3ea7ee255639f7db0957359795224f78594f187ce6","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"735f8551838c9dbf7bd44a3ea7ee255639f7db0957359795224f78594f187ce6","first_computed_at":"2026-05-18T00:14:33.915075Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:14:33.915075Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"tjoqMnohLCbMko2gYG6Ia2rKelmpaCn0Ma9S77FbOImopXKkbwI46OsbA/K6Vd2BI69262Z/MyeFJDbepN3FDg==","signature_status":"signed_v1","signed_at":"2026-05-18T00:14:33.915897Z","signed_message":"canonical_sha256_bytes"},"source_id":"1803.07640","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:1015aacbbae62ca0b9d3be94da56d8c385df649eb2b1aeeabeb86c7dfe7f0e4b","sha256:d813ca8006def13e1ff3623c00bfc24c752f69d048aaa6f0e922dc0fc4aea71e"],"state_sha256":"901c224329bce4137b6eec20287c9d688801c0808d7983da8199ac5e28792952"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"burGDPL/DUE0UNwnbCjj+ZqOCg+mLmLLQf+4Bsm9PL/fDXsDmay1SXk9SECiJbYeZhJDU/qWJYEZSDBVrj8NAw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-20T00:02:22.565247Z","bundle_sha256":"d916f6d3ec6c8db4e8348d77c5fe5f6609338b2a884ec27bb48fcadf3253d07b"}}