{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:3TRE6KEDLQ5XZTOMRYNHYOMMOX","short_pith_number":"pith:3TRE6KED","canonical_record":{"source":{"id":"2303.10368","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-03-18T08:57:09Z","cross_cats_sorted":[],"title_canon_sha256":"f5fc6a1175db324977372bbef81736a7933d850a463680b257d2f89ffc6e98ce","abstract_canon_sha256":"bfbfb4036d293191cd0dfa93c73412497a3c4e22cfebe2dc3257f08e1298ae67"},"schema_version":"1.0"},"canonical_sha256":"dce24f28835c3b7ccdcc8e1a7c398c75c1ce9e1efa120bea57730de5897a464c","source":{"kind":"arxiv","id":"2303.10368","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2303.10368","created_at":"2026-07-05T05:52:31Z"},{"alias_kind":"arxiv_version","alias_value":"2303.10368v1","created_at":"2026-07-05T05:52:31Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2303.10368","created_at":"2026-07-05T05:52:31Z"},{"alias_kind":"pith_short_12","alias_value":"3TRE6KEDLQ5X","created_at":"2026-07-05T05:52:31Z"},{"alias_kind":"pith_short_16","alias_value":"3TRE6KEDLQ5XZTOM","created_at":"2026-07-05T05:52:31Z"},{"alias_kind":"pith_short_8","alias_value":"3TRE6KED","created_at":"2026-07-05T05:52:31Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:3TRE6KEDLQ5XZTOMRYNHYOMMOX","target":"record","payload":{"canonical_record":{"source":{"id":"2303.10368","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-03-18T08:57:09Z","cross_cats_sorted":[],"title_canon_sha256":"f5fc6a1175db324977372bbef81736a7933d850a463680b257d2f89ffc6e98ce","abstract_canon_sha256":"bfbfb4036d293191cd0dfa93c73412497a3c4e22cfebe2dc3257f08e1298ae67"},"schema_version":"1.0"},"canonical_sha256":"dce24f28835c3b7ccdcc8e1a7c398c75c1ce9e1efa120bea57730de5897a464c","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:52:31.484224Z","signature_b64":"xj1w2zqFMbNeic5jj0qBPFUCPWRUQZHxFTthodqUe6IJppfLX5zt+5qg9jam37KiYBypevLfkvxfp5eaUYdKAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"dce24f28835c3b7ccdcc8e1a7c398c75c1ce9e1efa120bea57730de5897a464c","last_reissued_at":"2026-07-05T05:52:31.483823Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:52:31.483823Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2303.10368","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":"2026-07-05T05:52:31Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"PoHcH7b4zjsdbvCq8b9GRoj0Px1jn1NQwUm/DOcqTH9292xAyLaz+O8kRltIXaifvyX5BxSAvj3B9+fA6NjDAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-14T12:26:52.194573Z"},"content_sha256":"d08c525d9a51ea1957f1e97b5bbb72ad926a7964bda46282f865c5aa64c0cb8a","schema_version":"1.0","event_id":"sha256:d08c525d9a51ea1957f1e97b5bbb72ad926a7964bda46282f865c5aa64c0cb8a"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:3TRE6KEDLQ5XZTOMRYNHYOMMOX","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"An Empirical Study of Pre-trained Language Models in Simple Knowledge Graph Question Answering","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Dehai Min, Guilin Qi, Jeff Z. Pan, Jiaoyan Chen, Nan Hu, Yike Wu, Zafar Ali","submitted_at":"2023-03-18T08:57:09Z","abstract_excerpt":"Large-scale pre-trained language models (PLMs) such as BERT have recently achieved great success and become a milestone in natural language processing (NLP). It is now the consensus of the NLP community to adopt PLMs as the backbone for downstream tasks. In recent works on knowledge graph question answering (KGQA), BERT or its variants have become necessary in their KGQA models. However, there is still a lack of comprehensive research and comparison of the performance of different PLMs in KGQA. To this end, we summarize two basic KGQA frameworks based on PLMs without additional neural network "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2303.10368","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/2303.10368/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":"2026-07-05T05:52:31Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"5jGF0oCzfOvO9omixSJ2a4suNyvyAVknqKJRB9h5SODFNU5ErizMVJsBz1T2EBq7e5MfnZqpIV/65QkqMfhYDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-14T12:26:52.195080Z"},"content_sha256":"9eefe734bb4f849e8e26a74eb4229dc03fedb4702919452ff5a1223f2094fc14","schema_version":"1.0","event_id":"sha256:9eefe734bb4f849e8e26a74eb4229dc03fedb4702919452ff5a1223f2094fc14"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/3TRE6KEDLQ5XZTOMRYNHYOMMOX/bundle.json","state_url":"https://pith.science/pith/3TRE6KEDLQ5XZTOMRYNHYOMMOX/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/3TRE6KEDLQ5XZTOMRYNHYOMMOX/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":"2026-08-14T12:26:52Z","links":{"resolver":"https://pith.science/pith/3TRE6KEDLQ5XZTOMRYNHYOMMOX","bundle":"https://pith.science/pith/3TRE6KEDLQ5XZTOMRYNHYOMMOX/bundle.json","state":"https://pith.science/pith/3TRE6KEDLQ5XZTOMRYNHYOMMOX/state.json","well_known_bundle":"https://pith.science/.well-known/pith/3TRE6KEDLQ5XZTOMRYNHYOMMOX/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:3TRE6KEDLQ5XZTOMRYNHYOMMOX","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":"bfbfb4036d293191cd0dfa93c73412497a3c4e22cfebe2dc3257f08e1298ae67","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-03-18T08:57:09Z","title_canon_sha256":"f5fc6a1175db324977372bbef81736a7933d850a463680b257d2f89ffc6e98ce"},"schema_version":"1.0","source":{"id":"2303.10368","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2303.10368","created_at":"2026-07-05T05:52:31Z"},{"alias_kind":"arxiv_version","alias_value":"2303.10368v1","created_at":"2026-07-05T05:52:31Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2303.10368","created_at":"2026-07-05T05:52:31Z"},{"alias_kind":"pith_short_12","alias_value":"3TRE6KEDLQ5X","created_at":"2026-07-05T05:52:31Z"},{"alias_kind":"pith_short_16","alias_value":"3TRE6KEDLQ5XZTOM","created_at":"2026-07-05T05:52:31Z"},{"alias_kind":"pith_short_8","alias_value":"3TRE6KED","created_at":"2026-07-05T05:52:31Z"}],"graph_snapshots":[{"event_id":"sha256:9eefe734bb4f849e8e26a74eb4229dc03fedb4702919452ff5a1223f2094fc14","target":"graph","created_at":"2026-07-05T05:52:31Z","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/2303.10368/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Large-scale pre-trained language models (PLMs) such as BERT have recently achieved great success and become a milestone in natural language processing (NLP). It is now the consensus of the NLP community to adopt PLMs as the backbone for downstream tasks. In recent works on knowledge graph question answering (KGQA), BERT or its variants have become necessary in their KGQA models. However, there is still a lack of comprehensive research and comparison of the performance of different PLMs in KGQA. To this end, we summarize two basic KGQA frameworks based on PLMs without additional neural network ","authors_text":"Dehai Min, Guilin Qi, Jeff Z. Pan, Jiaoyan Chen, Nan Hu, Yike Wu, Zafar Ali","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-03-18T08:57:09Z","title":"An Empirical Study of Pre-trained Language Models in Simple Knowledge Graph Question Answering"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2303.10368","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:d08c525d9a51ea1957f1e97b5bbb72ad926a7964bda46282f865c5aa64c0cb8a","target":"record","created_at":"2026-07-05T05:52:31Z","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":"bfbfb4036d293191cd0dfa93c73412497a3c4e22cfebe2dc3257f08e1298ae67","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-03-18T08:57:09Z","title_canon_sha256":"f5fc6a1175db324977372bbef81736a7933d850a463680b257d2f89ffc6e98ce"},"schema_version":"1.0","source":{"id":"2303.10368","kind":"arxiv","version":1}},"canonical_sha256":"dce24f28835c3b7ccdcc8e1a7c398c75c1ce9e1efa120bea57730de5897a464c","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"dce24f28835c3b7ccdcc8e1a7c398c75c1ce9e1efa120bea57730de5897a464c","first_computed_at":"2026-07-05T05:52:31.483823Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:52:31.483823Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"xj1w2zqFMbNeic5jj0qBPFUCPWRUQZHxFTthodqUe6IJppfLX5zt+5qg9jam37KiYBypevLfkvxfp5eaUYdKAw==","signature_status":"signed_v1","signed_at":"2026-07-05T05:52:31.484224Z","signed_message":"canonical_sha256_bytes"},"source_id":"2303.10368","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:d08c525d9a51ea1957f1e97b5bbb72ad926a7964bda46282f865c5aa64c0cb8a","sha256:9eefe734bb4f849e8e26a74eb4229dc03fedb4702919452ff5a1223f2094fc14"],"state_sha256":"73d6c4b0ee76c353faca97b41c94c4522ad129adbfe484a44aeb374ec8ff0987"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"YJOOs8FW08B09dAWcF/w8PAyQzyAnwFK18AjBGeZYmrQcDrur0sgYiQdg0x43M1E2xPKtnORj6+WNg+i2SvHCw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-14T12:26:52.207898Z","bundle_sha256":"e702b1719f7c4706654da0f39cb2c850b7ddd9063cefa319076cf098dd417d95"}}