{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:EQCVPAFPGHFL4K2HXQWZCET6N2","short_pith_number":"pith:EQCVPAFP","canonical_record":{"source":{"id":"2207.02424","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2022-07-06T03:50:31Z","cross_cats_sorted":["cs.IR"],"title_canon_sha256":"321983572bf07ce1e234803dd172001ae7c9ee653d645345e4bcee288754e73f","abstract_canon_sha256":"c15fe4a26c2471c3915bfdcb973ccd011a46ec684e3b6d4af4556d9f4a8b95c2"},"schema_version":"1.0"},"canonical_sha256":"24055780af31cabe2b47bc2d91127e6ea473e12279f2bbd8ef2eda2ad9bb4962","source":{"kind":"arxiv","id":"2207.02424","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2207.02424","created_at":"2026-07-05T04:38:16Z"},{"alias_kind":"arxiv_version","alias_value":"2207.02424v2","created_at":"2026-07-05T04:38:16Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2207.02424","created_at":"2026-07-05T04:38:16Z"},{"alias_kind":"pith_short_12","alias_value":"EQCVPAFPGHFL","created_at":"2026-07-05T04:38:16Z"},{"alias_kind":"pith_short_16","alias_value":"EQCVPAFPGHFL4K2H","created_at":"2026-07-05T04:38:16Z"},{"alias_kind":"pith_short_8","alias_value":"EQCVPAFP","created_at":"2026-07-05T04:38:16Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:EQCVPAFPGHFL4K2HXQWZCET6N2","target":"record","payload":{"canonical_record":{"source":{"id":"2207.02424","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2022-07-06T03:50:31Z","cross_cats_sorted":["cs.IR"],"title_canon_sha256":"321983572bf07ce1e234803dd172001ae7c9ee653d645345e4bcee288754e73f","abstract_canon_sha256":"c15fe4a26c2471c3915bfdcb973ccd011a46ec684e3b6d4af4556d9f4a8b95c2"},"schema_version":"1.0"},"canonical_sha256":"24055780af31cabe2b47bc2d91127e6ea473e12279f2bbd8ef2eda2ad9bb4962","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T04:38:16.415460Z","signature_b64":"AcZP9AQzsFIK9SvarcMum2VoI2PA5VWNQExH1CWZMHmYL6muYG4aXtiHzDUyiDBYgi6w4k7HKiyg96RSYYUZAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"24055780af31cabe2b47bc2d91127e6ea473e12279f2bbd8ef2eda2ad9bb4962","last_reissued_at":"2026-07-05T04:38:16.414943Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T04:38:16.414943Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2207.02424","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":"2026-07-05T04:38:16Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"nJCRsCpeTJC4+deTCBTTyTYBbQwgSn45xX0X7Fu7pgIwFNN1m+YgEQdGRtnKMm5wZ1lWjZ7VoJwgli9PCvXNCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-01T13:50:25.610657Z"},"content_sha256":"269ec50c230b2eca51d00458759115c84e3768736f0fc23fbcccf00a7ea9653b","schema_version":"1.0","event_id":"sha256:269ec50c230b2eca51d00458759115c84e3768736f0fc23fbcccf00a7ea9653b"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:EQCVPAFPGHFL4K2HXQWZCET6N2","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Aspect-Based Sentiment Analysis using Local Context Focus Mechanism with DeBERTa","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.IR"],"primary_cat":"cs.CL","authors_text":"Ang Li, Junping Du, Tianyu Zhao, Zeli Guan, Zhe Xue","submitted_at":"2022-07-06T03:50:31Z","abstract_excerpt":"Text sentiment analysis, also known as opinion mining, is research on the calculation of people's views, evaluations, attitude and emotions expressed by entities. Text sentiment analysis can be divided into text-level sentiment analysis, sen-tence-level sentiment analysis and aspect-level sentiment analysis. Aspect-Based Sentiment Analysis (ABSA) is a fine-grained task in the field of sentiment analysis, which aims to predict the polarity of aspects. The research of pre-training neural model has significantly improved the performance of many natural language processing tasks. In recent years, "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2207.02424","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2207.02424/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":"2026-07-05T04:38:16Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"B5NtCpFVsTYOAyDd3lImcfWJoa8s9YYuLwmgNSAUM5084KSfrJLJQar9z1v9g/STJx29Gn7TKwY6Mv7xv+a/Dg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-01T13:50:25.611545Z"},"content_sha256":"566973e053c25ae5205a43fc1ba860b1d264c490c7e06e5db0b8395d8987a8b8","schema_version":"1.0","event_id":"sha256:566973e053c25ae5205a43fc1ba860b1d264c490c7e06e5db0b8395d8987a8b8"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/EQCVPAFPGHFL4K2HXQWZCET6N2/bundle.json","state_url":"https://pith.science/pith/EQCVPAFPGHFL4K2HXQWZCET6N2/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/EQCVPAFPGHFL4K2HXQWZCET6N2/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":"2026-08-01T13:50:25Z","links":{"resolver":"https://pith.science/pith/EQCVPAFPGHFL4K2HXQWZCET6N2","bundle":"https://pith.science/pith/EQCVPAFPGHFL4K2HXQWZCET6N2/bundle.json","state":"https://pith.science/pith/EQCVPAFPGHFL4K2HXQWZCET6N2/state.json","well_known_bundle":"https://pith.science/.well-known/pith/EQCVPAFPGHFL4K2HXQWZCET6N2/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:EQCVPAFPGHFL4K2HXQWZCET6N2","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":"c15fe4a26c2471c3915bfdcb973ccd011a46ec684e3b6d4af4556d9f4a8b95c2","cross_cats_sorted":["cs.IR"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2022-07-06T03:50:31Z","title_canon_sha256":"321983572bf07ce1e234803dd172001ae7c9ee653d645345e4bcee288754e73f"},"schema_version":"1.0","source":{"id":"2207.02424","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2207.02424","created_at":"2026-07-05T04:38:16Z"},{"alias_kind":"arxiv_version","alias_value":"2207.02424v2","created_at":"2026-07-05T04:38:16Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2207.02424","created_at":"2026-07-05T04:38:16Z"},{"alias_kind":"pith_short_12","alias_value":"EQCVPAFPGHFL","created_at":"2026-07-05T04:38:16Z"},{"alias_kind":"pith_short_16","alias_value":"EQCVPAFPGHFL4K2H","created_at":"2026-07-05T04:38:16Z"},{"alias_kind":"pith_short_8","alias_value":"EQCVPAFP","created_at":"2026-07-05T04:38:16Z"}],"graph_snapshots":[{"event_id":"sha256:566973e053c25ae5205a43fc1ba860b1d264c490c7e06e5db0b8395d8987a8b8","target":"graph","created_at":"2026-07-05T04:38:16Z","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/2207.02424/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Text sentiment analysis, also known as opinion mining, is research on the calculation of people's views, evaluations, attitude and emotions expressed by entities. Text sentiment analysis can be divided into text-level sentiment analysis, sen-tence-level sentiment analysis and aspect-level sentiment analysis. Aspect-Based Sentiment Analysis (ABSA) is a fine-grained task in the field of sentiment analysis, which aims to predict the polarity of aspects. The research of pre-training neural model has significantly improved the performance of many natural language processing tasks. In recent years, ","authors_text":"Ang Li, Junping Du, Tianyu Zhao, Zeli Guan, Zhe Xue","cross_cats":["cs.IR"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2022-07-06T03:50:31Z","title":"Aspect-Based Sentiment Analysis using Local Context Focus Mechanism with DeBERTa"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2207.02424","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":"sha256:269ec50c230b2eca51d00458759115c84e3768736f0fc23fbcccf00a7ea9653b","target":"record","created_at":"2026-07-05T04:38:16Z","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":"c15fe4a26c2471c3915bfdcb973ccd011a46ec684e3b6d4af4556d9f4a8b95c2","cross_cats_sorted":["cs.IR"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2022-07-06T03:50:31Z","title_canon_sha256":"321983572bf07ce1e234803dd172001ae7c9ee653d645345e4bcee288754e73f"},"schema_version":"1.0","source":{"id":"2207.02424","kind":"arxiv","version":2}},"canonical_sha256":"24055780af31cabe2b47bc2d91127e6ea473e12279f2bbd8ef2eda2ad9bb4962","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"24055780af31cabe2b47bc2d91127e6ea473e12279f2bbd8ef2eda2ad9bb4962","first_computed_at":"2026-07-05T04:38:16.414943Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T04:38:16.414943Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"AcZP9AQzsFIK9SvarcMum2VoI2PA5VWNQExH1CWZMHmYL6muYG4aXtiHzDUyiDBYgi6w4k7HKiyg96RSYYUZAg==","signature_status":"signed_v1","signed_at":"2026-07-05T04:38:16.415460Z","signed_message":"canonical_sha256_bytes"},"source_id":"2207.02424","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:269ec50c230b2eca51d00458759115c84e3768736f0fc23fbcccf00a7ea9653b","sha256:566973e053c25ae5205a43fc1ba860b1d264c490c7e06e5db0b8395d8987a8b8"],"state_sha256":"a5ce15d607165b1302d03eda20a0b59e371d5c8b01106fb2c33f8b4f60fd7e9c"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"JBV/W8h5ZN2cD32c1bC3Cq7liv0+xIdHxDNyFnwtWlUFHva/UrNp45SwIr2NFKmwKzzO90TnQu7NPOhaHlt0BA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-01T13:50:25.620641Z","bundle_sha256":"55b30d7db95c37beb419106dfc2319b2e68898ff1e5890134e8a39cca7ee7aaf"}}