{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2016:527FPT6NFSZULYCIN7MGLJQ2P6","short_pith_number":"pith:527FPT6N","canonical_record":{"source":{"id":"1604.05525","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2016-04-19T11:39:53Z","cross_cats_sorted":[],"title_canon_sha256":"07c8d0c6fa942c6024c8211260ba56980d8fe07a99afb2482ce9f237f866826d","abstract_canon_sha256":"97a72c5af1121e41ec3f71654d2e42fbf1951ec2042dbb2618be1b508893a4af"},"schema_version":"1.0"},"canonical_sha256":"eebe57cfcd2cb345e0486fd865a61a7f831e6ce836f76a6d1a8f0f082b5d5ca7","source":{"kind":"arxiv","id":"1604.05525","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1604.05525","created_at":"2026-05-18T01:16:38Z"},{"alias_kind":"arxiv_version","alias_value":"1604.05525v1","created_at":"2026-05-18T01:16:38Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1604.05525","created_at":"2026-05-18T01:16:38Z"},{"alias_kind":"pith_short_12","alias_value":"527FPT6NFSZU","created_at":"2026-05-18T12:29:58Z"},{"alias_kind":"pith_short_16","alias_value":"527FPT6NFSZULYCI","created_at":"2026-05-18T12:29:58Z"},{"alias_kind":"pith_short_8","alias_value":"527FPT6N","created_at":"2026-05-18T12:29:58Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2016:527FPT6NFSZULYCIN7MGLJQ2P6","target":"record","payload":{"canonical_record":{"source":{"id":"1604.05525","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2016-04-19T11:39:53Z","cross_cats_sorted":[],"title_canon_sha256":"07c8d0c6fa942c6024c8211260ba56980d8fe07a99afb2482ce9f237f866826d","abstract_canon_sha256":"97a72c5af1121e41ec3f71654d2e42fbf1951ec2042dbb2618be1b508893a4af"},"schema_version":"1.0"},"canonical_sha256":"eebe57cfcd2cb345e0486fd865a61a7f831e6ce836f76a6d1a8f0f082b5d5ca7","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T01:16:38.511483Z","signature_b64":"IBbzDumi3+LLz+uoMgMUtcSvGfSMfZpIySe5sB/2hK6yKvVMxIeGUYA7QhQGB2Jn2PSO8+rNEsQDaIxaC+IRBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"eebe57cfcd2cb345e0486fd865a61a7f831e6ce836f76a6d1a8f0f082b5d5ca7","last_reissued_at":"2026-05-18T01:16:38.510841Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T01:16:38.510841Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1604.05525","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":"2026-05-18T01:16:38Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"zQ2yIDg5Xggwz1It65A3Um+Px8Pt3hoqcirhiprbZsnwk9wj+hB3x3s2ZXezrxG9NwPLzFtS70qFJUKAV46FBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-19T08:09:29.387170Z"},"content_sha256":"d52a7c99a9872b63c1a8791b1e503ed182b208162b82a402f6daeb08070b562d","schema_version":"1.0","event_id":"sha256:d52a7c99a9872b63c1a8791b1e503ed182b208162b82a402f6daeb08070b562d"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2016:527FPT6NFSZULYCIN7MGLJQ2P6","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"An Attentive Neural Architecture for Fine-grained Entity Type Classification","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Kentaro Inui, Pontus Stenetorp, Sebastian Riedel, Sonse Shimaoka","submitted_at":"2016-04-19T11:39:53Z","abstract_excerpt":"In this work we propose a novel attention-based neural network model for the task of fine-grained entity type classification that unlike previously proposed models recursively composes representations of entity mention contexts. Our model achieves state-of-the-art performance with 74.94% loose micro F1-score on the well-established FIGER dataset, a relative improvement of 2.59%. We also investigate the behavior of the attention mechanism of our model and observe that it can learn contextual linguistic expressions that indicate the fine-grained category memberships of an entity."},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1604.05525","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":""},"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":"2026-05-18T01:16:38Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"sWtjm61GDRwrrHY6+vkoPnYvXKDReP4r1yBskz3JZ1o3ykNqeX8B9wZ20eHw9nIkfBn4PJm6aqhoFOxNpIKmBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-19T08:09:29.387854Z"},"content_sha256":"d7d87c261292ffb5e0cea1f825294d6ca3c99b79eb9db621663663b4ae3bfacd","schema_version":"1.0","event_id":"sha256:d7d87c261292ffb5e0cea1f825294d6ca3c99b79eb9db621663663b4ae3bfacd"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/527FPT6NFSZULYCIN7MGLJQ2P6/bundle.json","state_url":"https://pith.science/pith/527FPT6NFSZULYCIN7MGLJQ2P6/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/527FPT6NFSZULYCIN7MGLJQ2P6/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":"2026-05-19T08:09:29Z","links":{"resolver":"https://pith.science/pith/527FPT6NFSZULYCIN7MGLJQ2P6","bundle":"https://pith.science/pith/527FPT6NFSZULYCIN7MGLJQ2P6/bundle.json","state":"https://pith.science/pith/527FPT6NFSZULYCIN7MGLJQ2P6/state.json","well_known_bundle":"https://pith.science/.well-known/pith/527FPT6NFSZULYCIN7MGLJQ2P6/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2016:527FPT6NFSZULYCIN7MGLJQ2P6","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":"97a72c5af1121e41ec3f71654d2e42fbf1951ec2042dbb2618be1b508893a4af","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2016-04-19T11:39:53Z","title_canon_sha256":"07c8d0c6fa942c6024c8211260ba56980d8fe07a99afb2482ce9f237f866826d"},"schema_version":"1.0","source":{"id":"1604.05525","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1604.05525","created_at":"2026-05-18T01:16:38Z"},{"alias_kind":"arxiv_version","alias_value":"1604.05525v1","created_at":"2026-05-18T01:16:38Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1604.05525","created_at":"2026-05-18T01:16:38Z"},{"alias_kind":"pith_short_12","alias_value":"527FPT6NFSZU","created_at":"2026-05-18T12:29:58Z"},{"alias_kind":"pith_short_16","alias_value":"527FPT6NFSZULYCI","created_at":"2026-05-18T12:29:58Z"},{"alias_kind":"pith_short_8","alias_value":"527FPT6N","created_at":"2026-05-18T12:29:58Z"}],"graph_snapshots":[{"event_id":"sha256:d7d87c261292ffb5e0cea1f825294d6ca3c99b79eb9db621663663b4ae3bfacd","target":"graph","created_at":"2026-05-18T01:16:38Z","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":"In this work we propose a novel attention-based neural network model for the task of fine-grained entity type classification that unlike previously proposed models recursively composes representations of entity mention contexts. Our model achieves state-of-the-art performance with 74.94% loose micro F1-score on the well-established FIGER dataset, a relative improvement of 2.59%. We also investigate the behavior of the attention mechanism of our model and observe that it can learn contextual linguistic expressions that indicate the fine-grained category memberships of an entity.","authors_text":"Kentaro Inui, Pontus Stenetorp, Sebastian Riedel, Sonse Shimaoka","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2016-04-19T11:39:53Z","title":"An Attentive Neural Architecture for Fine-grained Entity Type Classification"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1604.05525","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:d52a7c99a9872b63c1a8791b1e503ed182b208162b82a402f6daeb08070b562d","target":"record","created_at":"2026-05-18T01:16:38Z","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":"97a72c5af1121e41ec3f71654d2e42fbf1951ec2042dbb2618be1b508893a4af","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2016-04-19T11:39:53Z","title_canon_sha256":"07c8d0c6fa942c6024c8211260ba56980d8fe07a99afb2482ce9f237f866826d"},"schema_version":"1.0","source":{"id":"1604.05525","kind":"arxiv","version":1}},"canonical_sha256":"eebe57cfcd2cb345e0486fd865a61a7f831e6ce836f76a6d1a8f0f082b5d5ca7","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"eebe57cfcd2cb345e0486fd865a61a7f831e6ce836f76a6d1a8f0f082b5d5ca7","first_computed_at":"2026-05-18T01:16:38.510841Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T01:16:38.510841Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"IBbzDumi3+LLz+uoMgMUtcSvGfSMfZpIySe5sB/2hK6yKvVMxIeGUYA7QhQGB2Jn2PSO8+rNEsQDaIxaC+IRBg==","signature_status":"signed_v1","signed_at":"2026-05-18T01:16:38.511483Z","signed_message":"canonical_sha256_bytes"},"source_id":"1604.05525","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:d52a7c99a9872b63c1a8791b1e503ed182b208162b82a402f6daeb08070b562d","sha256:d7d87c261292ffb5e0cea1f825294d6ca3c99b79eb9db621663663b4ae3bfacd"],"state_sha256":"42139858b4c654452c0a47b63805968805fbcfa08d62f08ebbddbd81e88ea1d7"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"FI/U2Dcq+hyXnvsxOvZVEtUFzehrj7C/Lvk9ALpgLJmfXIBSvLRN1C/GaLLrq9iGMDNdpqUD9simmiMu7QqzBA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-19T08:09:29.390783Z","bundle_sha256":"e08531e647702d875343ed3d3cfd6ec2175fa908d4408b77418b783169b91e8e"}}