{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:TIDDYD47BGUFQSFFXJ7EJALWSM","short_pith_number":"pith:TIDDYD47","canonical_record":{"source":{"id":"1909.02606","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2019-09-05T19:20:27Z","cross_cats_sorted":[],"title_canon_sha256":"253e2504abca32e7202848a51c23bb77425b103283c653eb781d753c965b2f77","abstract_canon_sha256":"4ea4b7582dfbaae233397826794b168ef97a49df423c361aa55457d5956267b5"},"schema_version":"1.0"},"canonical_sha256":"9a063c0f9f09a85848a5ba7e44817693201d45f2a923d956a1a53115a152b862","source":{"kind":"arxiv","id":"1909.02606","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1909.02606","created_at":"2026-07-05T00:02:41Z"},{"alias_kind":"arxiv_version","alias_value":"1909.02606v1","created_at":"2026-07-05T00:02:41Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1909.02606","created_at":"2026-07-05T00:02:41Z"},{"alias_kind":"pith_short_12","alias_value":"TIDDYD47BGUF","created_at":"2026-07-05T00:02:41Z"},{"alias_kind":"pith_short_16","alias_value":"TIDDYD47BGUFQSFF","created_at":"2026-07-05T00:02:41Z"},{"alias_kind":"pith_short_8","alias_value":"TIDDYD47","created_at":"2026-07-05T00:02:41Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:TIDDYD47BGUFQSFFXJ7EJALWSM","target":"record","payload":{"canonical_record":{"source":{"id":"1909.02606","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2019-09-05T19:20:27Z","cross_cats_sorted":[],"title_canon_sha256":"253e2504abca32e7202848a51c23bb77425b103283c653eb781d753c965b2f77","abstract_canon_sha256":"4ea4b7582dfbaae233397826794b168ef97a49df423c361aa55457d5956267b5"},"schema_version":"1.0"},"canonical_sha256":"9a063c0f9f09a85848a5ba7e44817693201d45f2a923d956a1a53115a152b862","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T00:02:41.031764Z","signature_b64":"KAYK/Pjvy9TLB+d5sgfkGHnqzLNMi/LuzL+QgPqfXS4B5i9jjwZCK/cuV888lbdAnlHPvtb6OJM1SRvZ7gGKBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"9a063c0f9f09a85848a5ba7e44817693201d45f2a923d956a1a53115a152b862","last_reissued_at":"2026-07-05T00:02:41.031385Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T00:02:41.031385Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1909.02606","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":"2026-07-05T00:02:41Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"jsqDHBpoKjkR3PNFyWjmVD57CJCPL9TJ2pqRYtxi5xg46qesVZlmONDwyjIl3L/j53dsz/YuOgBQvNFNt3IfCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-23T05:02:41.022193Z"},"content_sha256":"da7259441817af26dd67091f4db235681584b9b00175131547ccd23071c876f4","schema_version":"1.0","event_id":"sha256:da7259441817af26dd67091f4db235681584b9b00175131547ccd23071c876f4"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:TIDDYD47BGUFQSFFXJ7EJALWSM","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Syntax-Aware Aspect Level Sentiment Classification with Graph Attention Networks","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Binxuan Huang, Kathleen M. Carley","submitted_at":"2019-09-05T19:20:27Z","abstract_excerpt":"Aspect level sentiment classification aims to identify the sentiment expressed towards an aspect given a context sentence. Previous neural network based methods largely ignore the syntax structure in one sentence. In this paper, we propose a novel target-dependent graph attention network (TD-GAT) for aspect level sentiment classification, which explicitly utilizes the dependency relationship among words. Using the dependency graph, it propagates sentiment features directly from the syntactic context of an aspect target. In our experiments, we show our method outperforms multiple baselines with"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1909.02606","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/1909.02606/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":"2026-07-05T00:02:41Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ApqHCLSR6Nl0/ANlT2mc+eulGGWD9ksWuLLsXubAMRDzdvIW7X7QPfv0o8kr/pLoCNil1vtyUF5hq3uqpM8yDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-23T05:02:41.022776Z"},"content_sha256":"7006f7fbb3fa9940408a52cfcf41be4c56d3d1f848b4234234ceb0161ccf60a9","schema_version":"1.0","event_id":"sha256:7006f7fbb3fa9940408a52cfcf41be4c56d3d1f848b4234234ceb0161ccf60a9"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/TIDDYD47BGUFQSFFXJ7EJALWSM/bundle.json","state_url":"https://pith.science/pith/TIDDYD47BGUFQSFFXJ7EJALWSM/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/TIDDYD47BGUFQSFFXJ7EJALWSM/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":"2026-08-23T05:02:41Z","links":{"resolver":"https://pith.science/pith/TIDDYD47BGUFQSFFXJ7EJALWSM","bundle":"https://pith.science/pith/TIDDYD47BGUFQSFFXJ7EJALWSM/bundle.json","state":"https://pith.science/pith/TIDDYD47BGUFQSFFXJ7EJALWSM/state.json","well_known_bundle":"https://pith.science/.well-known/pith/TIDDYD47BGUFQSFFXJ7EJALWSM/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:TIDDYD47BGUFQSFFXJ7EJALWSM","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":"4ea4b7582dfbaae233397826794b168ef97a49df423c361aa55457d5956267b5","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2019-09-05T19:20:27Z","title_canon_sha256":"253e2504abca32e7202848a51c23bb77425b103283c653eb781d753c965b2f77"},"schema_version":"1.0","source":{"id":"1909.02606","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1909.02606","created_at":"2026-07-05T00:02:41Z"},{"alias_kind":"arxiv_version","alias_value":"1909.02606v1","created_at":"2026-07-05T00:02:41Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1909.02606","created_at":"2026-07-05T00:02:41Z"},{"alias_kind":"pith_short_12","alias_value":"TIDDYD47BGUF","created_at":"2026-07-05T00:02:41Z"},{"alias_kind":"pith_short_16","alias_value":"TIDDYD47BGUFQSFF","created_at":"2026-07-05T00:02:41Z"},{"alias_kind":"pith_short_8","alias_value":"TIDDYD47","created_at":"2026-07-05T00:02:41Z"}],"graph_snapshots":[{"event_id":"sha256:7006f7fbb3fa9940408a52cfcf41be4c56d3d1f848b4234234ceb0161ccf60a9","target":"graph","created_at":"2026-07-05T00:02:41Z","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/1909.02606/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Aspect level sentiment classification aims to identify the sentiment expressed towards an aspect given a context sentence. Previous neural network based methods largely ignore the syntax structure in one sentence. In this paper, we propose a novel target-dependent graph attention network (TD-GAT) for aspect level sentiment classification, which explicitly utilizes the dependency relationship among words. Using the dependency graph, it propagates sentiment features directly from the syntactic context of an aspect target. In our experiments, we show our method outperforms multiple baselines with","authors_text":"Binxuan Huang, Kathleen M. Carley","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2019-09-05T19:20:27Z","title":"Syntax-Aware Aspect Level Sentiment Classification with Graph Attention Networks"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1909.02606","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:da7259441817af26dd67091f4db235681584b9b00175131547ccd23071c876f4","target":"record","created_at":"2026-07-05T00:02:41Z","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":"4ea4b7582dfbaae233397826794b168ef97a49df423c361aa55457d5956267b5","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2019-09-05T19:20:27Z","title_canon_sha256":"253e2504abca32e7202848a51c23bb77425b103283c653eb781d753c965b2f77"},"schema_version":"1.0","source":{"id":"1909.02606","kind":"arxiv","version":1}},"canonical_sha256":"9a063c0f9f09a85848a5ba7e44817693201d45f2a923d956a1a53115a152b862","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"9a063c0f9f09a85848a5ba7e44817693201d45f2a923d956a1a53115a152b862","first_computed_at":"2026-07-05T00:02:41.031385Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T00:02:41.031385Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"KAYK/Pjvy9TLB+d5sgfkGHnqzLNMi/LuzL+QgPqfXS4B5i9jjwZCK/cuV888lbdAnlHPvtb6OJM1SRvZ7gGKBg==","signature_status":"signed_v1","signed_at":"2026-07-05T00:02:41.031764Z","signed_message":"canonical_sha256_bytes"},"source_id":"1909.02606","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:da7259441817af26dd67091f4db235681584b9b00175131547ccd23071c876f4","sha256:7006f7fbb3fa9940408a52cfcf41be4c56d3d1f848b4234234ceb0161ccf60a9"],"state_sha256":"e9d7c20488a8dcd79cbbde82d1fa11b1e2b93f444d6a4796614731ec8546855c"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"XIwZjmJOSfsbBxgV5Pfp8hKnvg/pl3mzmyDEWY8syvtgV7JiJhBLjLa2OeK0CZpnJ0pupU8Pb1HkKL6MOzsVBA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-23T05:02:41.027379Z","bundle_sha256":"c942e3037b1eb954ce7b56699bebfe9a4711945e809c5beba9f92f908b18344c"}}