{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2017:E6RSB2LRSTPBSS7V5RXPXHLT4G","short_pith_number":"pith:E6RSB2LR","canonical_record":{"source":{"id":"1711.04436","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2017-11-13T06:41:29Z","cross_cats_sorted":["cs.AI","cs.DB"],"title_canon_sha256":"dc51f89369a96789deda66b4f0850aee9206abeb7a8888eabd70c8440e2bb3a7","abstract_canon_sha256":"96c2ad8d7546cbaea2bbd229a0827cc91d056d0f2ca7cc65a5afe29a21928cba"},"schema_version":"1.0"},"canonical_sha256":"27a320e97194de194bf5ec6efb9d73e1983e1df00465d3274250045cf5718bee","source":{"kind":"arxiv","id":"1711.04436","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1711.04436","created_at":"2026-05-18T00:30:39Z"},{"alias_kind":"arxiv_version","alias_value":"1711.04436v1","created_at":"2026-05-18T00:30:39Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1711.04436","created_at":"2026-05-18T00:30:39Z"},{"alias_kind":"pith_short_12","alias_value":"E6RSB2LRSTPB","created_at":"2026-05-18T12:31:12Z"},{"alias_kind":"pith_short_16","alias_value":"E6RSB2LRSTPBSS7V","created_at":"2026-05-18T12:31:12Z"},{"alias_kind":"pith_short_8","alias_value":"E6RSB2LR","created_at":"2026-05-18T12:31:12Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2017:E6RSB2LRSTPBSS7V5RXPXHLT4G","target":"record","payload":{"canonical_record":{"source":{"id":"1711.04436","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2017-11-13T06:41:29Z","cross_cats_sorted":["cs.AI","cs.DB"],"title_canon_sha256":"dc51f89369a96789deda66b4f0850aee9206abeb7a8888eabd70c8440e2bb3a7","abstract_canon_sha256":"96c2ad8d7546cbaea2bbd229a0827cc91d056d0f2ca7cc65a5afe29a21928cba"},"schema_version":"1.0"},"canonical_sha256":"27a320e97194de194bf5ec6efb9d73e1983e1df00465d3274250045cf5718bee","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:30:39.027331Z","signature_b64":"7sFAL9O48lha/i3oyRvpUHSdJwdUU9tVJQmozlipEQKm3biNpukN9yDIsuUoi7Te4sNB/M2p+X711+L7dccKAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"27a320e97194de194bf5ec6efb9d73e1983e1df00465d3274250045cf5718bee","last_reissued_at":"2026-05-18T00:30:39.026565Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:30:39.026565Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1711.04436","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":"2026-05-18T00:30:39Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"kbhaj6e/vjWSTU7DUAM/OnDSNwkZLqZFvQAOaDoHNEFKvUoBIcd7s6oHtIMR1iyfU88MmiUlPzI7OqYd70ogBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-30T14:41:43.463131Z"},"content_sha256":"64bb8b2e0e6cafc4c1c8a75481e329aa693ab7faa0f748820590471a0c4f0800","schema_version":"1.0","event_id":"sha256:64bb8b2e0e6cafc4c1c8a75481e329aa693ab7faa0f748820590471a0c4f0800"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2017:E6RSB2LRSTPBSS7V5RXPXHLT4G","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"SQLNet: Generating Structured Queries From Natural Language Without Reinforcement Learning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.DB"],"primary_cat":"cs.CL","authors_text":"Chang Liu, Dawn Song, Xiaojun Xu","submitted_at":"2017-11-13T06:41:29Z","abstract_excerpt":"Synthesizing SQL queries from natural language is a long-standing open problem and has been attracting considerable interest recently. Toward solving the problem, the de facto approach is to employ a sequence-to-sequence-style model. Such an approach will necessarily require the SQL queries to be serialized. Since the same SQL query may have multiple equivalent serializations, training a sequence-to-sequence-style model is sensitive to the choice from one of them. This phenomenon is documented as the \"order-matters\" problem. Existing state-of-the-art approaches rely on reinforcement learning t"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1711.04436","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":"2026-05-18T00:30:39Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"M0p33CrFvA+ZpLYO7BKgv3rBs1JMuv2y1en+fbVVVFvis+4Pm6J4g6ny5tORwDTFFzHJXPbh8LLm25uAiXqrDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-30T14:41:43.463495Z"},"content_sha256":"52a78b6e5cdd5a54a75e38db3139d625ff1cf4322b04b9165d0809c5f18e1d02","schema_version":"1.0","event_id":"sha256:52a78b6e5cdd5a54a75e38db3139d625ff1cf4322b04b9165d0809c5f18e1d02"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/E6RSB2LRSTPBSS7V5RXPXHLT4G/bundle.json","state_url":"https://pith.science/pith/E6RSB2LRSTPBSS7V5RXPXHLT4G/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/E6RSB2LRSTPBSS7V5RXPXHLT4G/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":"2026-05-30T14:41:43Z","links":{"resolver":"https://pith.science/pith/E6RSB2LRSTPBSS7V5RXPXHLT4G","bundle":"https://pith.science/pith/E6RSB2LRSTPBSS7V5RXPXHLT4G/bundle.json","state":"https://pith.science/pith/E6RSB2LRSTPBSS7V5RXPXHLT4G/state.json","well_known_bundle":"https://pith.science/.well-known/pith/E6RSB2LRSTPBSS7V5RXPXHLT4G/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:E6RSB2LRSTPBSS7V5RXPXHLT4G","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":"96c2ad8d7546cbaea2bbd229a0827cc91d056d0f2ca7cc65a5afe29a21928cba","cross_cats_sorted":["cs.AI","cs.DB"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2017-11-13T06:41:29Z","title_canon_sha256":"dc51f89369a96789deda66b4f0850aee9206abeb7a8888eabd70c8440e2bb3a7"},"schema_version":"1.0","source":{"id":"1711.04436","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1711.04436","created_at":"2026-05-18T00:30:39Z"},{"alias_kind":"arxiv_version","alias_value":"1711.04436v1","created_at":"2026-05-18T00:30:39Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1711.04436","created_at":"2026-05-18T00:30:39Z"},{"alias_kind":"pith_short_12","alias_value":"E6RSB2LRSTPB","created_at":"2026-05-18T12:31:12Z"},{"alias_kind":"pith_short_16","alias_value":"E6RSB2LRSTPBSS7V","created_at":"2026-05-18T12:31:12Z"},{"alias_kind":"pith_short_8","alias_value":"E6RSB2LR","created_at":"2026-05-18T12:31:12Z"}],"graph_snapshots":[{"event_id":"sha256:52a78b6e5cdd5a54a75e38db3139d625ff1cf4322b04b9165d0809c5f18e1d02","target":"graph","created_at":"2026-05-18T00:30:39Z","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":"Synthesizing SQL queries from natural language is a long-standing open problem and has been attracting considerable interest recently. Toward solving the problem, the de facto approach is to employ a sequence-to-sequence-style model. Such an approach will necessarily require the SQL queries to be serialized. Since the same SQL query may have multiple equivalent serializations, training a sequence-to-sequence-style model is sensitive to the choice from one of them. This phenomenon is documented as the \"order-matters\" problem. Existing state-of-the-art approaches rely on reinforcement learning t","authors_text":"Chang Liu, Dawn Song, Xiaojun Xu","cross_cats":["cs.AI","cs.DB"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2017-11-13T06:41:29Z","title":"SQLNet: Generating Structured Queries From Natural Language Without Reinforcement Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1711.04436","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":"sha256:64bb8b2e0e6cafc4c1c8a75481e329aa693ab7faa0f748820590471a0c4f0800","target":"record","created_at":"2026-05-18T00:30:39Z","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":"96c2ad8d7546cbaea2bbd229a0827cc91d056d0f2ca7cc65a5afe29a21928cba","cross_cats_sorted":["cs.AI","cs.DB"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2017-11-13T06:41:29Z","title_canon_sha256":"dc51f89369a96789deda66b4f0850aee9206abeb7a8888eabd70c8440e2bb3a7"},"schema_version":"1.0","source":{"id":"1711.04436","kind":"arxiv","version":1}},"canonical_sha256":"27a320e97194de194bf5ec6efb9d73e1983e1df00465d3274250045cf5718bee","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"27a320e97194de194bf5ec6efb9d73e1983e1df00465d3274250045cf5718bee","first_computed_at":"2026-05-18T00:30:39.026565Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:30:39.026565Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"7sFAL9O48lha/i3oyRvpUHSdJwdUU9tVJQmozlipEQKm3biNpukN9yDIsuUoi7Te4sNB/M2p+X711+L7dccKAA==","signature_status":"signed_v1","signed_at":"2026-05-18T00:30:39.027331Z","signed_message":"canonical_sha256_bytes"},"source_id":"1711.04436","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:64bb8b2e0e6cafc4c1c8a75481e329aa693ab7faa0f748820590471a0c4f0800","sha256:52a78b6e5cdd5a54a75e38db3139d625ff1cf4322b04b9165d0809c5f18e1d02"],"state_sha256":"9f52b0a2eeafaba8c4adbd86a1d34241c48205d05b728be5f837a6002b03d1e8"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"En9HMQsummFKdgpbB5y0uf16la9o1/62Uv0VB3UkQRSaB1lTzpVv3/1m5MCMsVa2TTnS8d2Q5vqT+SkH7xAvDg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-30T14:41:43.465891Z","bundle_sha256":"b1c98d5281c7a93e6289d18824999e436e957569daf0ef7e783132fdf634b925"}}