{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2017:YD4N5RGJGUMOADDQJC6MFZD2TE","short_pith_number":"pith:YD4N5RGJ","canonical_record":{"source":{"id":"1701.02901","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2017-01-11T09:32:47Z","cross_cats_sorted":[],"title_canon_sha256":"3e00d2e93ee01c8c77f5fbd962ae0e4cb9ba8a0ff524d4cf9d3b872e983bfa49","abstract_canon_sha256":"17ffe0f0dc622592a659effb3c88e6a67747d596a4d43cfa0c9598571dcdab6d"},"schema_version":"1.0"},"canonical_sha256":"c0f8dec4c93518e00c7048bcc2e47a991b995adb3d5c9c8ebf0810e2bea78e34","source":{"kind":"arxiv","id":"1701.02901","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1701.02901","created_at":"2026-05-18T00:52:59Z"},{"alias_kind":"arxiv_version","alias_value":"1701.02901v1","created_at":"2026-05-18T00:52:59Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1701.02901","created_at":"2026-05-18T00:52:59Z"},{"alias_kind":"pith_short_12","alias_value":"YD4N5RGJGUMO","created_at":"2026-05-18T12:31:56Z"},{"alias_kind":"pith_short_16","alias_value":"YD4N5RGJGUMOADDQ","created_at":"2026-05-18T12:31:56Z"},{"alias_kind":"pith_short_8","alias_value":"YD4N5RGJ","created_at":"2026-05-18T12:31:56Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2017:YD4N5RGJGUMOADDQJC6MFZD2TE","target":"record","payload":{"canonical_record":{"source":{"id":"1701.02901","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2017-01-11T09:32:47Z","cross_cats_sorted":[],"title_canon_sha256":"3e00d2e93ee01c8c77f5fbd962ae0e4cb9ba8a0ff524d4cf9d3b872e983bfa49","abstract_canon_sha256":"17ffe0f0dc622592a659effb3c88e6a67747d596a4d43cfa0c9598571dcdab6d"},"schema_version":"1.0"},"canonical_sha256":"c0f8dec4c93518e00c7048bcc2e47a991b995adb3d5c9c8ebf0810e2bea78e34","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:52:59.865044Z","signature_b64":"XTvKhHlH2UBYiGOJ4wd539R+JG/YSqaM7R89cJgCORgRVVm20bWuuHVBVIsAqJHr7b4V7MDNvWy3IMTrX+/BBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"c0f8dec4c93518e00c7048bcc2e47a991b995adb3d5c9c8ebf0810e2bea78e34","last_reissued_at":"2026-05-18T00:52:59.864612Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:52:59.864612Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1701.02901","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":"2026-05-18T00:52:59Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"AYayUGfEmx8PCEdEzgbE09po98NFd1LXLvLZuG/8U1cxVPekzhZNt72zZkTO8JH68mvG5pZ8MNjRH48l6AEFBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-25T21:28:08.179387Z"},"content_sha256":"dac4eda7cc0e7459e9c2f753db2ce6a9801257a184b3015432cdcd406c3b6d4e","schema_version":"1.0","event_id":"sha256:dac4eda7cc0e7459e9c2f753db2ce6a9801257a184b3015432cdcd406c3b6d4e"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2017:YD4N5RGJGUMOADDQJC6MFZD2TE","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"A Multifaceted Evaluation of Neural versus Phrase-Based Machine Translation for 9 Language Directions","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Antonio Toral, V\\'ictor M. S\\'anchez-Cartagena","submitted_at":"2017-01-11T09:32:47Z","abstract_excerpt":"We aim to shed light on the strengths and weaknesses of the newly introduced neural machine translation paradigm. To that end, we conduct a multifaceted evaluation in which we compare outputs produced by state-of-the-art neural machine translation and phrase-based machine translation systems for 9 language directions across a number of dimensions. Specifically, we measure the similarity of the outputs, their fluency and amount of reordering, the effect of sentence length and performance across different error categories. We find out that translations produced by neural machine translation syst"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1701.02901","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":"2026-05-18T00:52:59Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"BClp2DIVCFpDfYWt/cQvgU5XKroXnVwb7HbVMg11xjHI7wxz4uu+rxxj6yZo5tG/wR7uQhKfLtzxuQuDrtBFDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-25T21:28:08.179764Z"},"content_sha256":"d81c6979d0f7883562fa038432f2bd041605f480328a677189e61819b5c7be90","schema_version":"1.0","event_id":"sha256:d81c6979d0f7883562fa038432f2bd041605f480328a677189e61819b5c7be90"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/YD4N5RGJGUMOADDQJC6MFZD2TE/bundle.json","state_url":"https://pith.science/pith/YD4N5RGJGUMOADDQJC6MFZD2TE/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/YD4N5RGJGUMOADDQJC6MFZD2TE/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":"2026-05-25T21:28:08Z","links":{"resolver":"https://pith.science/pith/YD4N5RGJGUMOADDQJC6MFZD2TE","bundle":"https://pith.science/pith/YD4N5RGJGUMOADDQJC6MFZD2TE/bundle.json","state":"https://pith.science/pith/YD4N5RGJGUMOADDQJC6MFZD2TE/state.json","well_known_bundle":"https://pith.science/.well-known/pith/YD4N5RGJGUMOADDQJC6MFZD2TE/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:YD4N5RGJGUMOADDQJC6MFZD2TE","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":"17ffe0f0dc622592a659effb3c88e6a67747d596a4d43cfa0c9598571dcdab6d","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2017-01-11T09:32:47Z","title_canon_sha256":"3e00d2e93ee01c8c77f5fbd962ae0e4cb9ba8a0ff524d4cf9d3b872e983bfa49"},"schema_version":"1.0","source":{"id":"1701.02901","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1701.02901","created_at":"2026-05-18T00:52:59Z"},{"alias_kind":"arxiv_version","alias_value":"1701.02901v1","created_at":"2026-05-18T00:52:59Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1701.02901","created_at":"2026-05-18T00:52:59Z"},{"alias_kind":"pith_short_12","alias_value":"YD4N5RGJGUMO","created_at":"2026-05-18T12:31:56Z"},{"alias_kind":"pith_short_16","alias_value":"YD4N5RGJGUMOADDQ","created_at":"2026-05-18T12:31:56Z"},{"alias_kind":"pith_short_8","alias_value":"YD4N5RGJ","created_at":"2026-05-18T12:31:56Z"}],"graph_snapshots":[{"event_id":"sha256:d81c6979d0f7883562fa038432f2bd041605f480328a677189e61819b5c7be90","target":"graph","created_at":"2026-05-18T00:52:59Z","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":"We aim to shed light on the strengths and weaknesses of the newly introduced neural machine translation paradigm. To that end, we conduct a multifaceted evaluation in which we compare outputs produced by state-of-the-art neural machine translation and phrase-based machine translation systems for 9 language directions across a number of dimensions. Specifically, we measure the similarity of the outputs, their fluency and amount of reordering, the effect of sentence length and performance across different error categories. We find out that translations produced by neural machine translation syst","authors_text":"Antonio Toral, V\\'ictor M. S\\'anchez-Cartagena","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2017-01-11T09:32:47Z","title":"A Multifaceted Evaluation of Neural versus Phrase-Based Machine Translation for 9 Language Directions"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1701.02901","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:dac4eda7cc0e7459e9c2f753db2ce6a9801257a184b3015432cdcd406c3b6d4e","target":"record","created_at":"2026-05-18T00:52:59Z","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":"17ffe0f0dc622592a659effb3c88e6a67747d596a4d43cfa0c9598571dcdab6d","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2017-01-11T09:32:47Z","title_canon_sha256":"3e00d2e93ee01c8c77f5fbd962ae0e4cb9ba8a0ff524d4cf9d3b872e983bfa49"},"schema_version":"1.0","source":{"id":"1701.02901","kind":"arxiv","version":1}},"canonical_sha256":"c0f8dec4c93518e00c7048bcc2e47a991b995adb3d5c9c8ebf0810e2bea78e34","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"c0f8dec4c93518e00c7048bcc2e47a991b995adb3d5c9c8ebf0810e2bea78e34","first_computed_at":"2026-05-18T00:52:59.864612Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:52:59.864612Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"XTvKhHlH2UBYiGOJ4wd539R+JG/YSqaM7R89cJgCORgRVVm20bWuuHVBVIsAqJHr7b4V7MDNvWy3IMTrX+/BBQ==","signature_status":"signed_v1","signed_at":"2026-05-18T00:52:59.865044Z","signed_message":"canonical_sha256_bytes"},"source_id":"1701.02901","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:dac4eda7cc0e7459e9c2f753db2ce6a9801257a184b3015432cdcd406c3b6d4e","sha256:d81c6979d0f7883562fa038432f2bd041605f480328a677189e61819b5c7be90"],"state_sha256":"2090fd0a59dd69c38519f3c04cc45010321d018699036226584e9830b59749dc"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"RKbM5AKKyHHa/JZ0Nl8eyiblgcwqa3rI2PTv6kO7wZ/jqiBDPxtAyWd7co6fJzb1cU9X+PCSepNQ9BPPnbLBBg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-25T21:28:08.181930Z","bundle_sha256":"2341effd13b2b513cfed67c60118c20397b3e7765db135c6679bdf1cd71ede38"}}