{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:KNBNLLSY5VSFBCTAMSRBT6MKHR","short_pith_number":"pith:KNBNLLSY","canonical_record":{"source":{"id":"1906.02059","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2019-06-05T14:56:06Z","cross_cats_sorted":[],"title_canon_sha256":"016010eeb16eb27d0f9d9ab85404e31d6e04bb141a11d0cef68bf2ddf70e56fa","abstract_canon_sha256":"1ac0aa3bdc644fb1fe2f6448c39061d3ace2571b7f34717c3eec45385d33de80"},"schema_version":"1.0"},"canonical_sha256":"5342d5ae58ed64508a6064a219f98a3c4e36bd478829945fba42e93afb35a994","source":{"kind":"arxiv","id":"1906.02059","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1906.02059","created_at":"2026-05-17T23:44:05Z"},{"alias_kind":"arxiv_version","alias_value":"1906.02059v1","created_at":"2026-05-17T23:44:05Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1906.02059","created_at":"2026-05-17T23:44:05Z"},{"alias_kind":"pith_short_12","alias_value":"KNBNLLSY5VSF","created_at":"2026-05-18T12:33:21Z"},{"alias_kind":"pith_short_16","alias_value":"KNBNLLSY5VSFBCTA","created_at":"2026-05-18T12:33:21Z"},{"alias_kind":"pith_short_8","alias_value":"KNBNLLSY","created_at":"2026-05-18T12:33:21Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:KNBNLLSY5VSFBCTAMSRBT6MKHR","target":"record","payload":{"canonical_record":{"source":{"id":"1906.02059","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2019-06-05T14:56:06Z","cross_cats_sorted":[],"title_canon_sha256":"016010eeb16eb27d0f9d9ab85404e31d6e04bb141a11d0cef68bf2ddf70e56fa","abstract_canon_sha256":"1ac0aa3bdc644fb1fe2f6448c39061d3ace2571b7f34717c3eec45385d33de80"},"schema_version":"1.0"},"canonical_sha256":"5342d5ae58ed64508a6064a219f98a3c4e36bd478829945fba42e93afb35a994","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:44:05.360172Z","signature_b64":"dWsR4vJX2aoCwQJl4OkaPNAnBb/wfIXxa9JL88k5q6XHMbOsAiA3h7xMfTMP5LjKCvK8GugaHW8z9mdN43KlDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"5342d5ae58ed64508a6064a219f98a3c4e36bd478829945fba42e93afb35a994","last_reissued_at":"2026-05-17T23:44:05.359756Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:44:05.359756Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1906.02059","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":"2026-05-17T23:44:05Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"WLltj1jjEK93x8Vs+3gjQEIPM0QjoExAERtHDwLdJJCR4p8mzWMPMDe7BuFoYMIwc6Q0x9HEqEIlqbATfDhPDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-23T13:12:54.416169Z"},"content_sha256":"15cc5d55831a8061ad5a6f3eb6fd4e8da25cd74a7f0ccdaeddfc2d1c27ad42fc","schema_version":"1.0","event_id":"sha256:15cc5d55831a8061ad5a6f3eb6fd4e8da25cd74a7f0ccdaeddfc2d1c27ad42fc"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:KNBNLLSY5VSFBCTAMSRBT6MKHR","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Neural Legal Judgment Prediction in English","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Ilias Chalkidis, Ion Androutsopoulos, Nikolaos Aletras","submitted_at":"2019-06-05T14:56:06Z","abstract_excerpt":"Legal judgment prediction is the task of automatically predicting the outcome of a court case, given a text describing the case's facts. Previous work on using neural models for this task has focused on Chinese; only feature-based models (e.g., using bags of words and topics) have been considered in English. We release a new English legal judgment prediction dataset, containing cases from the European Court of Human Rights. We evaluate a broad variety of neural models on the new dataset, establishing strong baselines that surpass previous feature-based models in three tasks: (1) binary violati"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1906.02059","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":"2026-05-17T23:44:05Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"YZYAiIOivAFYad7WzcywxfVo/tFHIWBkA8PkOc9o+lpbINpEOM45gCwGv0drEAdQm1kgU8PxhnDwld1aF+IfBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-23T13:12:54.416805Z"},"content_sha256":"a2c5a2cd93abede87efb7ceecfa4b65898039b779ebf4cfc362f1127b49e51be","schema_version":"1.0","event_id":"sha256:a2c5a2cd93abede87efb7ceecfa4b65898039b779ebf4cfc362f1127b49e51be"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/KNBNLLSY5VSFBCTAMSRBT6MKHR/bundle.json","state_url":"https://pith.science/pith/KNBNLLSY5VSFBCTAMSRBT6MKHR/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/KNBNLLSY5VSFBCTAMSRBT6MKHR/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":"2026-05-23T13:12:54Z","links":{"resolver":"https://pith.science/pith/KNBNLLSY5VSFBCTAMSRBT6MKHR","bundle":"https://pith.science/pith/KNBNLLSY5VSFBCTAMSRBT6MKHR/bundle.json","state":"https://pith.science/pith/KNBNLLSY5VSFBCTAMSRBT6MKHR/state.json","well_known_bundle":"https://pith.science/.well-known/pith/KNBNLLSY5VSFBCTAMSRBT6MKHR/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:KNBNLLSY5VSFBCTAMSRBT6MKHR","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":"1ac0aa3bdc644fb1fe2f6448c39061d3ace2571b7f34717c3eec45385d33de80","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2019-06-05T14:56:06Z","title_canon_sha256":"016010eeb16eb27d0f9d9ab85404e31d6e04bb141a11d0cef68bf2ddf70e56fa"},"schema_version":"1.0","source":{"id":"1906.02059","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1906.02059","created_at":"2026-05-17T23:44:05Z"},{"alias_kind":"arxiv_version","alias_value":"1906.02059v1","created_at":"2026-05-17T23:44:05Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1906.02059","created_at":"2026-05-17T23:44:05Z"},{"alias_kind":"pith_short_12","alias_value":"KNBNLLSY5VSF","created_at":"2026-05-18T12:33:21Z"},{"alias_kind":"pith_short_16","alias_value":"KNBNLLSY5VSFBCTA","created_at":"2026-05-18T12:33:21Z"},{"alias_kind":"pith_short_8","alias_value":"KNBNLLSY","created_at":"2026-05-18T12:33:21Z"}],"graph_snapshots":[{"event_id":"sha256:a2c5a2cd93abede87efb7ceecfa4b65898039b779ebf4cfc362f1127b49e51be","target":"graph","created_at":"2026-05-17T23:44:05Z","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":"Legal judgment prediction is the task of automatically predicting the outcome of a court case, given a text describing the case's facts. Previous work on using neural models for this task has focused on Chinese; only feature-based models (e.g., using bags of words and topics) have been considered in English. We release a new English legal judgment prediction dataset, containing cases from the European Court of Human Rights. We evaluate a broad variety of neural models on the new dataset, establishing strong baselines that surpass previous feature-based models in three tasks: (1) binary violati","authors_text":"Ilias Chalkidis, Ion Androutsopoulos, Nikolaos Aletras","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2019-06-05T14:56:06Z","title":"Neural Legal Judgment Prediction in English"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1906.02059","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":"sha256:15cc5d55831a8061ad5a6f3eb6fd4e8da25cd74a7f0ccdaeddfc2d1c27ad42fc","target":"record","created_at":"2026-05-17T23:44:05Z","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":"1ac0aa3bdc644fb1fe2f6448c39061d3ace2571b7f34717c3eec45385d33de80","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2019-06-05T14:56:06Z","title_canon_sha256":"016010eeb16eb27d0f9d9ab85404e31d6e04bb141a11d0cef68bf2ddf70e56fa"},"schema_version":"1.0","source":{"id":"1906.02059","kind":"arxiv","version":1}},"canonical_sha256":"5342d5ae58ed64508a6064a219f98a3c4e36bd478829945fba42e93afb35a994","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"5342d5ae58ed64508a6064a219f98a3c4e36bd478829945fba42e93afb35a994","first_computed_at":"2026-05-17T23:44:05.359756Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:44:05.359756Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"dWsR4vJX2aoCwQJl4OkaPNAnBb/wfIXxa9JL88k5q6XHMbOsAiA3h7xMfTMP5LjKCvK8GugaHW8z9mdN43KlDQ==","signature_status":"signed_v1","signed_at":"2026-05-17T23:44:05.360172Z","signed_message":"canonical_sha256_bytes"},"source_id":"1906.02059","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:15cc5d55831a8061ad5a6f3eb6fd4e8da25cd74a7f0ccdaeddfc2d1c27ad42fc","sha256:a2c5a2cd93abede87efb7ceecfa4b65898039b779ebf4cfc362f1127b49e51be"],"state_sha256":"98ab8eb674b3040a698923f705b1aa3eaccd312c9ca17c730805b3801ceeb718"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"nNGN+f2RdbTRJuOwtdcIgwXIHR5dZ7zfu22IbDnjqcR8HcjPoJRR9tC8F/Loh+wKKczeoez+FAL2PRA3KO0mAQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-23T13:12:54.420376Z","bundle_sha256":"db11b2297db577de8faf4aae5083ac17d09816c33cecf444f2d8f4edd45e96c9"}}