{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2016:7L7B477NBEW2ZBCNLTVK2QCMF6","short_pith_number":"pith:7L7B477N","canonical_record":{"source":{"id":"1606.00210","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2016-06-01T10:32:28Z","cross_cats_sorted":[],"title_canon_sha256":"599ca0dfc0e849ac80922e5e8e9d82051ecf354432bf4c55a26c6a95b409247d","abstract_canon_sha256":"0e8c35fbea3ccba3bd19bdd20b4a4fcaeb44ca7e175b54f1439dd77bc7c24c20"},"schema_version":"1.0"},"canonical_sha256":"fafe1e7fed092dac844d5ceaad404c2fbc555264e98d5957a92c36da8910ce88","source":{"kind":"arxiv","id":"1606.00210","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1606.00210","created_at":"2026-05-18T01:13:05Z"},{"alias_kind":"arxiv_version","alias_value":"1606.00210v1","created_at":"2026-05-18T01:13:05Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1606.00210","created_at":"2026-05-18T01:13:05Z"},{"alias_kind":"pith_short_12","alias_value":"7L7B477NBEW2","created_at":"2026-05-18T12:30:04Z"},{"alias_kind":"pith_short_16","alias_value":"7L7B477NBEW2ZBCN","created_at":"2026-05-18T12:30:04Z"},{"alias_kind":"pith_short_8","alias_value":"7L7B477N","created_at":"2026-05-18T12:30:04Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2016:7L7B477NBEW2ZBCNLTVK2QCMF6","target":"record","payload":{"canonical_record":{"source":{"id":"1606.00210","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2016-06-01T10:32:28Z","cross_cats_sorted":[],"title_canon_sha256":"599ca0dfc0e849ac80922e5e8e9d82051ecf354432bf4c55a26c6a95b409247d","abstract_canon_sha256":"0e8c35fbea3ccba3bd19bdd20b4a4fcaeb44ca7e175b54f1439dd77bc7c24c20"},"schema_version":"1.0"},"canonical_sha256":"fafe1e7fed092dac844d5ceaad404c2fbc555264e98d5957a92c36da8910ce88","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T01:13:05.744331Z","signature_b64":"ZtKCDLnxgwTrV0CUizrSfIFXyeHR7WFStv+enImUazX/xMHpbaHPJ2DNKBV4/JJ4zNQuH7nEro0CyGAG4NNGBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"fafe1e7fed092dac844d5ceaad404c2fbc555264e98d5957a92c36da8910ce88","last_reissued_at":"2026-05-18T01:13:05.743943Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T01:13:05.743943Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1606.00210","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":"2026-05-18T01:13:05Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"+0ey3GDXUUFqavkO+7HtCqxGuTyTmaJKpwcvCZpOR9KqmxxON+EcuYPoM2On11S/i0NQ5qkwvkaKzPb09WouAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-14T19:37:10.641921Z"},"content_sha256":"98fbfa80984e54f3799b701df883497b2096e9718611bacdb302849014e6a5fd","schema_version":"1.0","event_id":"sha256:98fbfa80984e54f3799b701df883497b2096e9718611bacdb302849014e6a5fd"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2016:7L7B477NBEW2ZBCNLTVK2QCMF6","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Exploiting N-Best Hypotheses to Improve an SMT Approach to Grammatical Error Correction","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Duc Tam Hoang, Hwee Tou Ng, Shamil Chollampatt","submitted_at":"2016-06-01T10:32:28Z","abstract_excerpt":"Grammatical error correction (GEC) is the task of detecting and correcting grammatical errors in texts written by second language learners. The statistical machine translation (SMT) approach to GEC, in which sentences written by second language learners are translated to grammatically correct sentences, has achieved state-of-the-art accuracy. However, the SMT approach is unable to utilize global context. In this paper, we propose a novel approach to improve the accuracy of GEC, by exploiting the n-best hypotheses generated by an SMT approach. Specifically, we build a classifier to score the ed"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1606.00210","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":"2026-05-18T01:13:05Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"+Y+1oTcuoGhXmmXb9X5U3Wt2dQBeGEm2JFqN9W4V5hGQ0hQRqJdkd0RaeOlCd3m4Tz9nZjz/S6QPuwfZ7zTqBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-14T19:37:10.642380Z"},"content_sha256":"0336261d68cb25777c77adbbacad6f8d239c60e6eace6a4a3ede3a9b73c02116","schema_version":"1.0","event_id":"sha256:0336261d68cb25777c77adbbacad6f8d239c60e6eace6a4a3ede3a9b73c02116"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/7L7B477NBEW2ZBCNLTVK2QCMF6/bundle.json","state_url":"https://pith.science/pith/7L7B477NBEW2ZBCNLTVK2QCMF6/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/7L7B477NBEW2ZBCNLTVK2QCMF6/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":"2026-08-14T19:37:10Z","links":{"resolver":"https://pith.science/pith/7L7B477NBEW2ZBCNLTVK2QCMF6","bundle":"https://pith.science/pith/7L7B477NBEW2ZBCNLTVK2QCMF6/bundle.json","state":"https://pith.science/pith/7L7B477NBEW2ZBCNLTVK2QCMF6/state.json","well_known_bundle":"https://pith.science/.well-known/pith/7L7B477NBEW2ZBCNLTVK2QCMF6/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2016:7L7B477NBEW2ZBCNLTVK2QCMF6","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":"0e8c35fbea3ccba3bd19bdd20b4a4fcaeb44ca7e175b54f1439dd77bc7c24c20","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2016-06-01T10:32:28Z","title_canon_sha256":"599ca0dfc0e849ac80922e5e8e9d82051ecf354432bf4c55a26c6a95b409247d"},"schema_version":"1.0","source":{"id":"1606.00210","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1606.00210","created_at":"2026-05-18T01:13:05Z"},{"alias_kind":"arxiv_version","alias_value":"1606.00210v1","created_at":"2026-05-18T01:13:05Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1606.00210","created_at":"2026-05-18T01:13:05Z"},{"alias_kind":"pith_short_12","alias_value":"7L7B477NBEW2","created_at":"2026-05-18T12:30:04Z"},{"alias_kind":"pith_short_16","alias_value":"7L7B477NBEW2ZBCN","created_at":"2026-05-18T12:30:04Z"},{"alias_kind":"pith_short_8","alias_value":"7L7B477N","created_at":"2026-05-18T12:30:04Z"}],"graph_snapshots":[{"event_id":"sha256:0336261d68cb25777c77adbbacad6f8d239c60e6eace6a4a3ede3a9b73c02116","target":"graph","created_at":"2026-05-18T01:13:05Z","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":"Grammatical error correction (GEC) is the task of detecting and correcting grammatical errors in texts written by second language learners. The statistical machine translation (SMT) approach to GEC, in which sentences written by second language learners are translated to grammatically correct sentences, has achieved state-of-the-art accuracy. However, the SMT approach is unable to utilize global context. In this paper, we propose a novel approach to improve the accuracy of GEC, by exploiting the n-best hypotheses generated by an SMT approach. Specifically, we build a classifier to score the ed","authors_text":"Duc Tam Hoang, Hwee Tou Ng, Shamil Chollampatt","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2016-06-01T10:32:28Z","title":"Exploiting N-Best Hypotheses to Improve an SMT Approach to Grammatical Error Correction"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1606.00210","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":"sha256:98fbfa80984e54f3799b701df883497b2096e9718611bacdb302849014e6a5fd","target":"record","created_at":"2026-05-18T01:13:05Z","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":"0e8c35fbea3ccba3bd19bdd20b4a4fcaeb44ca7e175b54f1439dd77bc7c24c20","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2016-06-01T10:32:28Z","title_canon_sha256":"599ca0dfc0e849ac80922e5e8e9d82051ecf354432bf4c55a26c6a95b409247d"},"schema_version":"1.0","source":{"id":"1606.00210","kind":"arxiv","version":1}},"canonical_sha256":"fafe1e7fed092dac844d5ceaad404c2fbc555264e98d5957a92c36da8910ce88","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"fafe1e7fed092dac844d5ceaad404c2fbc555264e98d5957a92c36da8910ce88","first_computed_at":"2026-05-18T01:13:05.743943Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T01:13:05.743943Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"ZtKCDLnxgwTrV0CUizrSfIFXyeHR7WFStv+enImUazX/xMHpbaHPJ2DNKBV4/JJ4zNQuH7nEro0CyGAG4NNGBg==","signature_status":"signed_v1","signed_at":"2026-05-18T01:13:05.744331Z","signed_message":"canonical_sha256_bytes"},"source_id":"1606.00210","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:98fbfa80984e54f3799b701df883497b2096e9718611bacdb302849014e6a5fd","sha256:0336261d68cb25777c77adbbacad6f8d239c60e6eace6a4a3ede3a9b73c02116"],"state_sha256":"be04aeb507ae1faeb7f185c6782e942c71a675ed8165368846e556dbc373d6d1"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"KKvQLeRPBWvsxZRh+oA64XVqFFLJglLCjjiYI2cIsmj0zu1dwELHas/HxSQHURhtfonb5aNOTV2VcyuFus8PAw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-14T19:37:10.646996Z","bundle_sha256":"4aea7e6a123b5f8e7a2b5bf8a7e6b50bd85e2eabdde7d74c08240e7e9c5e7e7c"}}