{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2016:SKJSSNUGSDPMWGW7JZURUIRXFD","short_pith_number":"pith:SKJSSNUG","canonical_record":{"source":{"id":"1603.08884","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2016-03-29T18:52:46Z","cross_cats_sorted":[],"title_canon_sha256":"4e2ab89abc4f5ee783e12a225743275545aa4851309883667d640dc62cb75be6","abstract_canon_sha256":"53ce94f1073b0bbdcda4529cbb573ccaa003c0e7b4b7d519f0a8d1b69c872034"},"schema_version":"1.0"},"canonical_sha256":"929329368690decb1adf4e691a223728fa1be41d9e58e4b825718e0902e675c5","source":{"kind":"arxiv","id":"1603.08884","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1603.08884","created_at":"2026-05-18T01:18:05Z"},{"alias_kind":"arxiv_version","alias_value":"1603.08884v1","created_at":"2026-05-18T01:18:05Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1603.08884","created_at":"2026-05-18T01:18:05Z"},{"alias_kind":"pith_short_12","alias_value":"SKJSSNUGSDPM","created_at":"2026-05-18T12:30:44Z"},{"alias_kind":"pith_short_16","alias_value":"SKJSSNUGSDPMWGW7","created_at":"2026-05-18T12:30:44Z"},{"alias_kind":"pith_short_8","alias_value":"SKJSSNUG","created_at":"2026-05-18T12:30:44Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2016:SKJSSNUGSDPMWGW7JZURUIRXFD","target":"record","payload":{"canonical_record":{"source":{"id":"1603.08884","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2016-03-29T18:52:46Z","cross_cats_sorted":[],"title_canon_sha256":"4e2ab89abc4f5ee783e12a225743275545aa4851309883667d640dc62cb75be6","abstract_canon_sha256":"53ce94f1073b0bbdcda4529cbb573ccaa003c0e7b4b7d519f0a8d1b69c872034"},"schema_version":"1.0"},"canonical_sha256":"929329368690decb1adf4e691a223728fa1be41d9e58e4b825718e0902e675c5","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T01:18:05.084412Z","signature_b64":"UhYozRoo/Al7BYou1jx/j9ujCAFhaXL257/SDBVaufbEvvURYhCnjGB0qKnDCfmKBZdnVSILcHDElp+CH9lNDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"929329368690decb1adf4e691a223728fa1be41d9e58e4b825718e0902e675c5","last_reissued_at":"2026-05-18T01:18:05.083699Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T01:18:05.083699Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1603.08884","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":"2026-05-18T01:18:05Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"LJ1cEbnoxaply8zUgAOWScA9StMgxnIPxWm4QtYzbyLQx2ZaNzVsGfuGU/S+mD+6NY0uQoWCesEg4P88vBgIDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-30T01:16:07.102849Z"},"content_sha256":"96e1af86ea3cc5360b37e8bd368bcdfa022b979cc9d02688d994b3e8fbe2f08f","schema_version":"1.0","event_id":"sha256:96e1af86ea3cc5360b37e8bd368bcdfa022b979cc9d02688d994b3e8fbe2f08f"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2016:SKJSSNUGSDPMWGW7JZURUIRXFD","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"A Parallel-Hierarchical Model for Machine Comprehension on Sparse Data","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Adam Trischler, Jing He, Kaheer Suleman, Phillip Bachman, Xingdi Yuan, Zheng Ye","submitted_at":"2016-03-29T18:52:46Z","abstract_excerpt":"Understanding unstructured text is a major goal within natural language processing. Comprehension tests pose questions based on short text passages to evaluate such understanding. In this work, we investigate machine comprehension on the challenging {\\it MCTest} benchmark. Partly because of its limited size, prior work on {\\it MCTest} has focused mainly on engineering better features. We tackle the dataset with a neural approach, harnessing simple neural networks arranged in a parallel hierarchy. The parallel hierarchy enables our model to compare the passage, question, and answer from a varie"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1603.08884","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":"2026-05-18T01:18:05Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"A6pUjvAuvs4SXu0jshwn2UsO7Yy7+kln2rg96yPJ5cnsKV65XnrALc38rmeQmWKo4DHo1mh0YoMohcEqZYJuDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-30T01:16:07.103508Z"},"content_sha256":"87af9e0416d1a46f4398ffbe967b71fdaf41a72391fc52f7be5c687c66fbaa73","schema_version":"1.0","event_id":"sha256:87af9e0416d1a46f4398ffbe967b71fdaf41a72391fc52f7be5c687c66fbaa73"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/SKJSSNUGSDPMWGW7JZURUIRXFD/bundle.json","state_url":"https://pith.science/pith/SKJSSNUGSDPMWGW7JZURUIRXFD/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/SKJSSNUGSDPMWGW7JZURUIRXFD/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":"2026-05-30T01:16:07Z","links":{"resolver":"https://pith.science/pith/SKJSSNUGSDPMWGW7JZURUIRXFD","bundle":"https://pith.science/pith/SKJSSNUGSDPMWGW7JZURUIRXFD/bundle.json","state":"https://pith.science/pith/SKJSSNUGSDPMWGW7JZURUIRXFD/state.json","well_known_bundle":"https://pith.science/.well-known/pith/SKJSSNUGSDPMWGW7JZURUIRXFD/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2016:SKJSSNUGSDPMWGW7JZURUIRXFD","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":"53ce94f1073b0bbdcda4529cbb573ccaa003c0e7b4b7d519f0a8d1b69c872034","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2016-03-29T18:52:46Z","title_canon_sha256":"4e2ab89abc4f5ee783e12a225743275545aa4851309883667d640dc62cb75be6"},"schema_version":"1.0","source":{"id":"1603.08884","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1603.08884","created_at":"2026-05-18T01:18:05Z"},{"alias_kind":"arxiv_version","alias_value":"1603.08884v1","created_at":"2026-05-18T01:18:05Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1603.08884","created_at":"2026-05-18T01:18:05Z"},{"alias_kind":"pith_short_12","alias_value":"SKJSSNUGSDPM","created_at":"2026-05-18T12:30:44Z"},{"alias_kind":"pith_short_16","alias_value":"SKJSSNUGSDPMWGW7","created_at":"2026-05-18T12:30:44Z"},{"alias_kind":"pith_short_8","alias_value":"SKJSSNUG","created_at":"2026-05-18T12:30:44Z"}],"graph_snapshots":[{"event_id":"sha256:87af9e0416d1a46f4398ffbe967b71fdaf41a72391fc52f7be5c687c66fbaa73","target":"graph","created_at":"2026-05-18T01:18:05Z","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":"Understanding unstructured text is a major goal within natural language processing. Comprehension tests pose questions based on short text passages to evaluate such understanding. In this work, we investigate machine comprehension on the challenging {\\it MCTest} benchmark. Partly because of its limited size, prior work on {\\it MCTest} has focused mainly on engineering better features. We tackle the dataset with a neural approach, harnessing simple neural networks arranged in a parallel hierarchy. The parallel hierarchy enables our model to compare the passage, question, and answer from a varie","authors_text":"Adam Trischler, Jing He, Kaheer Suleman, Phillip Bachman, Xingdi Yuan, Zheng Ye","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2016-03-29T18:52:46Z","title":"A Parallel-Hierarchical Model for Machine Comprehension on Sparse Data"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1603.08884","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":"sha256:96e1af86ea3cc5360b37e8bd368bcdfa022b979cc9d02688d994b3e8fbe2f08f","target":"record","created_at":"2026-05-18T01:18:05Z","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":"53ce94f1073b0bbdcda4529cbb573ccaa003c0e7b4b7d519f0a8d1b69c872034","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2016-03-29T18:52:46Z","title_canon_sha256":"4e2ab89abc4f5ee783e12a225743275545aa4851309883667d640dc62cb75be6"},"schema_version":"1.0","source":{"id":"1603.08884","kind":"arxiv","version":1}},"canonical_sha256":"929329368690decb1adf4e691a223728fa1be41d9e58e4b825718e0902e675c5","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"929329368690decb1adf4e691a223728fa1be41d9e58e4b825718e0902e675c5","first_computed_at":"2026-05-18T01:18:05.083699Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T01:18:05.083699Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"UhYozRoo/Al7BYou1jx/j9ujCAFhaXL257/SDBVaufbEvvURYhCnjGB0qKnDCfmKBZdnVSILcHDElp+CH9lNDw==","signature_status":"signed_v1","signed_at":"2026-05-18T01:18:05.084412Z","signed_message":"canonical_sha256_bytes"},"source_id":"1603.08884","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:96e1af86ea3cc5360b37e8bd368bcdfa022b979cc9d02688d994b3e8fbe2f08f","sha256:87af9e0416d1a46f4398ffbe967b71fdaf41a72391fc52f7be5c687c66fbaa73"],"state_sha256":"41996f847d5a4ec62ef7f753920b89f325473c66a8963339b5cd80b6890745bc"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"7r8F4jBpptsdnsxOEODtLtto5rhWL/vjAJMSpYKhhIlRnMKmYeNzq4BwQnCWisC+PYNjuS+D9vyRNx3iFiFrDw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-30T01:16:07.107144Z","bundle_sha256":"2968422cfa1db6ab14a858d24c42a3bc967c871d92c3fe1ec07c4326ea177bd0"}}