{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:M3JWSZAAL6LLJ3GDTYUMAJJERJ","short_pith_number":"pith:M3JWSZAA","canonical_record":{"source":{"id":"1905.09052","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IR","submitted_at":"2019-05-22T10:13:48Z","cross_cats_sorted":["cs.CL"],"title_canon_sha256":"00bed34bcef26f5ad1a4980f8b09c40103da095baeab49503786e940a5134f48","abstract_canon_sha256":"3a8ef8d45418574fba514f1f52c6d6deeb6df2495e38e898d7201e76de7bbdae"},"schema_version":"1.0"},"canonical_sha256":"66d36964005f96b4ecc39e28c025248a5bb2f0aa2a95f6b4224fc1b289c0c0b1","source":{"kind":"arxiv","id":"1905.09052","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1905.09052","created_at":"2026-05-17T23:45:22Z"},{"alias_kind":"arxiv_version","alias_value":"1905.09052v1","created_at":"2026-05-17T23:45:22Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1905.09052","created_at":"2026-05-17T23:45:22Z"},{"alias_kind":"pith_short_12","alias_value":"M3JWSZAAL6LL","created_at":"2026-05-18T12:33:21Z"},{"alias_kind":"pith_short_16","alias_value":"M3JWSZAAL6LLJ3GD","created_at":"2026-05-18T12:33:21Z"},{"alias_kind":"pith_short_8","alias_value":"M3JWSZAA","created_at":"2026-05-18T12:33:21Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:M3JWSZAAL6LLJ3GDTYUMAJJERJ","target":"record","payload":{"canonical_record":{"source":{"id":"1905.09052","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IR","submitted_at":"2019-05-22T10:13:48Z","cross_cats_sorted":["cs.CL"],"title_canon_sha256":"00bed34bcef26f5ad1a4980f8b09c40103da095baeab49503786e940a5134f48","abstract_canon_sha256":"3a8ef8d45418574fba514f1f52c6d6deeb6df2495e38e898d7201e76de7bbdae"},"schema_version":"1.0"},"canonical_sha256":"66d36964005f96b4ecc39e28c025248a5bb2f0aa2a95f6b4224fc1b289c0c0b1","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:45:22.097829Z","signature_b64":"UdPR5GwxGPe3NZTkZHVSiudZwzXWzYHXn94saEhr/H3sFSNpeiq8LO/DTeClh1h6jitmBdBcHCdF2NDjD/HoBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"66d36964005f96b4ecc39e28c025248a5bb2f0aa2a95f6b4224fc1b289c0c0b1","last_reissued_at":"2026-05-17T23:45:22.097274Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:45:22.097274Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1905.09052","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":"2026-05-17T23:45:22Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"/aIK0vUqqmoQPKakJ6I7cgjFuuTVcRiXia2+BxOH4Iy6m72CAsf1ZCbrP+ULGa+sBZzA4ZZBjx8nULegJu5kBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-08T16:20:47.630120Z"},"content_sha256":"237a1e7ac27b4a3ce5334124ed3602c21d6370356b5a5132a90f595bccd921e7","schema_version":"1.0","event_id":"sha256:237a1e7ac27b4a3ce5334124ed3602c21d6370356b5a5132a90f595bccd921e7"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:M3JWSZAAL6LLJ3GDTYUMAJJERJ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Retrieving Multi-Entity Associations: An Evaluation of Combination Modes for Word Embeddings","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CL"],"primary_cat":"cs.IR","authors_text":"Andreas Spitz, Gloria Feher, Michael Gertz","submitted_at":"2019-05-22T10:13:48Z","abstract_excerpt":"Word embeddings have gained significant attention as learnable representations of semantic relations between words, and have been shown to improve upon the results of traditional word representations. However, little effort has been devoted to using embeddings for the retrieval of entity associations beyond pairwise relations. In this paper, we use popular embedding methods to train vector representations of an entity-annotated news corpus, and evaluate their performance for the task of predicting entity participation in news events versus a traditional word cooccurrence network as a baseline."},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1905.09052","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":"2026-05-17T23:45:22Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"FIPp+SoybJCpm4t0ORk866VojDJQCVUAW1ajw5iB0RKG02MVQP9bIGS14jBTSNXfNdQ2/Zk1xhwfQK3TjnplAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-08T16:20:47.630492Z"},"content_sha256":"ef854b66317bfad0157826d9867ea5249d44adc71740fcb5a0abed87ed62133f","schema_version":"1.0","event_id":"sha256:ef854b66317bfad0157826d9867ea5249d44adc71740fcb5a0abed87ed62133f"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/M3JWSZAAL6LLJ3GDTYUMAJJERJ/bundle.json","state_url":"https://pith.science/pith/M3JWSZAAL6LLJ3GDTYUMAJJERJ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/M3JWSZAAL6LLJ3GDTYUMAJJERJ/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":"2026-07-08T16:20:47Z","links":{"resolver":"https://pith.science/pith/M3JWSZAAL6LLJ3GDTYUMAJJERJ","bundle":"https://pith.science/pith/M3JWSZAAL6LLJ3GDTYUMAJJERJ/bundle.json","state":"https://pith.science/pith/M3JWSZAAL6LLJ3GDTYUMAJJERJ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/M3JWSZAAL6LLJ3GDTYUMAJJERJ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:M3JWSZAAL6LLJ3GDTYUMAJJERJ","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":"3a8ef8d45418574fba514f1f52c6d6deeb6df2495e38e898d7201e76de7bbdae","cross_cats_sorted":["cs.CL"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IR","submitted_at":"2019-05-22T10:13:48Z","title_canon_sha256":"00bed34bcef26f5ad1a4980f8b09c40103da095baeab49503786e940a5134f48"},"schema_version":"1.0","source":{"id":"1905.09052","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1905.09052","created_at":"2026-05-17T23:45:22Z"},{"alias_kind":"arxiv_version","alias_value":"1905.09052v1","created_at":"2026-05-17T23:45:22Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1905.09052","created_at":"2026-05-17T23:45:22Z"},{"alias_kind":"pith_short_12","alias_value":"M3JWSZAAL6LL","created_at":"2026-05-18T12:33:21Z"},{"alias_kind":"pith_short_16","alias_value":"M3JWSZAAL6LLJ3GD","created_at":"2026-05-18T12:33:21Z"},{"alias_kind":"pith_short_8","alias_value":"M3JWSZAA","created_at":"2026-05-18T12:33:21Z"}],"graph_snapshots":[{"event_id":"sha256:ef854b66317bfad0157826d9867ea5249d44adc71740fcb5a0abed87ed62133f","target":"graph","created_at":"2026-05-17T23:45:22Z","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":"Word embeddings have gained significant attention as learnable representations of semantic relations between words, and have been shown to improve upon the results of traditional word representations. However, little effort has been devoted to using embeddings for the retrieval of entity associations beyond pairwise relations. In this paper, we use popular embedding methods to train vector representations of an entity-annotated news corpus, and evaluate their performance for the task of predicting entity participation in news events versus a traditional word cooccurrence network as a baseline.","authors_text":"Andreas Spitz, Gloria Feher, Michael Gertz","cross_cats":["cs.CL"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IR","submitted_at":"2019-05-22T10:13:48Z","title":"Retrieving Multi-Entity Associations: An Evaluation of Combination Modes for Word Embeddings"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1905.09052","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":"sha256:237a1e7ac27b4a3ce5334124ed3602c21d6370356b5a5132a90f595bccd921e7","target":"record","created_at":"2026-05-17T23:45:22Z","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":"3a8ef8d45418574fba514f1f52c6d6deeb6df2495e38e898d7201e76de7bbdae","cross_cats_sorted":["cs.CL"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IR","submitted_at":"2019-05-22T10:13:48Z","title_canon_sha256":"00bed34bcef26f5ad1a4980f8b09c40103da095baeab49503786e940a5134f48"},"schema_version":"1.0","source":{"id":"1905.09052","kind":"arxiv","version":1}},"canonical_sha256":"66d36964005f96b4ecc39e28c025248a5bb2f0aa2a95f6b4224fc1b289c0c0b1","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"66d36964005f96b4ecc39e28c025248a5bb2f0aa2a95f6b4224fc1b289c0c0b1","first_computed_at":"2026-05-17T23:45:22.097274Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:45:22.097274Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"UdPR5GwxGPe3NZTkZHVSiudZwzXWzYHXn94saEhr/H3sFSNpeiq8LO/DTeClh1h6jitmBdBcHCdF2NDjD/HoBw==","signature_status":"signed_v1","signed_at":"2026-05-17T23:45:22.097829Z","signed_message":"canonical_sha256_bytes"},"source_id":"1905.09052","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:237a1e7ac27b4a3ce5334124ed3602c21d6370356b5a5132a90f595bccd921e7","sha256:ef854b66317bfad0157826d9867ea5249d44adc71740fcb5a0abed87ed62133f"],"state_sha256":"6d618011ddd990f753c922433fdf2a08dfdb4357e7b56eee146f318f35be7e9b"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"7aOfU31by3IR4u71ilS9tpF96OmaYJwcGFJstSsfma7j0z3lfA7rGX+zqpowXiiK7Hevck1ufUOgNNgf7ZeDBw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-08T16:20:47.632451Z","bundle_sha256":"0e40e25d9c0d5c03c44d5e0437d141c2290fbe67e229caf43b87437e3f35ffc2"}}