{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:QDDDISFGCILUYDA327BPUMNG3I","short_pith_number":"pith:QDDDISFG","canonical_record":{"source":{"id":"1801.10442","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-01-31T13:25:29Z","cross_cats_sorted":[],"title_canon_sha256":"e5c04cef53c8af8f13df859234d1c15f10b19ef8cbf635c60a7d32fdb4e208ac","abstract_canon_sha256":"32dfefe3a7f97fc8b124ee2d0bfa1a34671765dcf2f85ce9fea901c80516b7aa"},"schema_version":"1.0"},"canonical_sha256":"80c63448a612174c0c1bd7c2fa31a6da11729ca16d4cc3994ce5e3eeb0a6a6cd","source":{"kind":"arxiv","id":"1801.10442","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1801.10442","created_at":"2026-05-18T00:24:40Z"},{"alias_kind":"arxiv_version","alias_value":"1801.10442v1","created_at":"2026-05-18T00:24:40Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1801.10442","created_at":"2026-05-18T00:24:40Z"},{"alias_kind":"pith_short_12","alias_value":"QDDDISFGCILU","created_at":"2026-05-18T12:32:46Z"},{"alias_kind":"pith_short_16","alias_value":"QDDDISFGCILUYDA3","created_at":"2026-05-18T12:32:46Z"},{"alias_kind":"pith_short_8","alias_value":"QDDDISFG","created_at":"2026-05-18T12:32:46Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:QDDDISFGCILUYDA327BPUMNG3I","target":"record","payload":{"canonical_record":{"source":{"id":"1801.10442","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-01-31T13:25:29Z","cross_cats_sorted":[],"title_canon_sha256":"e5c04cef53c8af8f13df859234d1c15f10b19ef8cbf635c60a7d32fdb4e208ac","abstract_canon_sha256":"32dfefe3a7f97fc8b124ee2d0bfa1a34671765dcf2f85ce9fea901c80516b7aa"},"schema_version":"1.0"},"canonical_sha256":"80c63448a612174c0c1bd7c2fa31a6da11729ca16d4cc3994ce5e3eeb0a6a6cd","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:24:40.807666Z","signature_b64":"ycLAoXvRFlidGaT/ZZgehHRApKUqI46HcBxnsahnJbY7YcpBmNay7YLnITZi5WUG/ESQpE9QmihaOvxW3NSzDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"80c63448a612174c0c1bd7c2fa31a6da11729ca16d4cc3994ce5e3eeb0a6a6cd","last_reissued_at":"2026-05-18T00:24:40.806910Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:24:40.806910Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1801.10442","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":"2026-05-18T00:24:40Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"RJX/ODWGEGOkdJVH6MrIcsl/tKlh06t0vuj+Y0DOzY92SWhX1FwvtVtNMgrXZHM+H8rXOPIJ45jyK6uunbcuDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-31T16:52:40.529671Z"},"content_sha256":"0ddc1f51201915974b14b98e22d9ee5078656d0d5f25ef5708e083e61b875e9e","schema_version":"1.0","event_id":"sha256:0ddc1f51201915974b14b98e22d9ee5078656d0d5f25ef5708e083e61b875e9e"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:QDDDISFGCILUYDA327BPUMNG3I","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"From Benedict Cumberbatch to Sherlock Holmes: Character Identification in TV series without a Script","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Andrew Zisserman, Arsha Nagrani","submitted_at":"2018-01-31T13:25:29Z","abstract_excerpt":"The goal of this paper is the automatic identification of characters in TV and feature film material. In contrast to standard approaches to this task, which rely on the weak supervision afforded by transcripts and subtitles, we propose a new method requiring only a cast list. This list is used to obtain images of actors from freely available sources on the web, providing a form of partial supervision for this task. In using images of actors to recognize characters, we make the following three contributions: (i) We demonstrate that an automated semi-supervised learning approach is able to adapt"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1801.10442","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":"2026-05-18T00:24:40Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"HtntqHg82lTWz4U+0Pt9KuWmjFNw0qoZAv+QuZDjCHY/pid3rf1GOhAy9ybNX8Ulq0GrS0brfYPAtSoCkP1tAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-31T16:52:40.530350Z"},"content_sha256":"3f1302aa34b74589cb9d565faf5f2ddc598b03acd84fcf41de4e63ed2b4ac25a","schema_version":"1.0","event_id":"sha256:3f1302aa34b74589cb9d565faf5f2ddc598b03acd84fcf41de4e63ed2b4ac25a"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/QDDDISFGCILUYDA327BPUMNG3I/bundle.json","state_url":"https://pith.science/pith/QDDDISFGCILUYDA327BPUMNG3I/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/QDDDISFGCILUYDA327BPUMNG3I/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":"2026-05-31T16:52:40Z","links":{"resolver":"https://pith.science/pith/QDDDISFGCILUYDA327BPUMNG3I","bundle":"https://pith.science/pith/QDDDISFGCILUYDA327BPUMNG3I/bundle.json","state":"https://pith.science/pith/QDDDISFGCILUYDA327BPUMNG3I/state.json","well_known_bundle":"https://pith.science/.well-known/pith/QDDDISFGCILUYDA327BPUMNG3I/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:QDDDISFGCILUYDA327BPUMNG3I","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":"32dfefe3a7f97fc8b124ee2d0bfa1a34671765dcf2f85ce9fea901c80516b7aa","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-01-31T13:25:29Z","title_canon_sha256":"e5c04cef53c8af8f13df859234d1c15f10b19ef8cbf635c60a7d32fdb4e208ac"},"schema_version":"1.0","source":{"id":"1801.10442","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1801.10442","created_at":"2026-05-18T00:24:40Z"},{"alias_kind":"arxiv_version","alias_value":"1801.10442v1","created_at":"2026-05-18T00:24:40Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1801.10442","created_at":"2026-05-18T00:24:40Z"},{"alias_kind":"pith_short_12","alias_value":"QDDDISFGCILU","created_at":"2026-05-18T12:32:46Z"},{"alias_kind":"pith_short_16","alias_value":"QDDDISFGCILUYDA3","created_at":"2026-05-18T12:32:46Z"},{"alias_kind":"pith_short_8","alias_value":"QDDDISFG","created_at":"2026-05-18T12:32:46Z"}],"graph_snapshots":[{"event_id":"sha256:3f1302aa34b74589cb9d565faf5f2ddc598b03acd84fcf41de4e63ed2b4ac25a","target":"graph","created_at":"2026-05-18T00:24:40Z","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":"The goal of this paper is the automatic identification of characters in TV and feature film material. In contrast to standard approaches to this task, which rely on the weak supervision afforded by transcripts and subtitles, we propose a new method requiring only a cast list. This list is used to obtain images of actors from freely available sources on the web, providing a form of partial supervision for this task. In using images of actors to recognize characters, we make the following three contributions: (i) We demonstrate that an automated semi-supervised learning approach is able to adapt","authors_text":"Andrew Zisserman, Arsha Nagrani","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-01-31T13:25:29Z","title":"From Benedict Cumberbatch to Sherlock Holmes: Character Identification in TV series without a Script"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1801.10442","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":"sha256:0ddc1f51201915974b14b98e22d9ee5078656d0d5f25ef5708e083e61b875e9e","target":"record","created_at":"2026-05-18T00:24:40Z","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":"32dfefe3a7f97fc8b124ee2d0bfa1a34671765dcf2f85ce9fea901c80516b7aa","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-01-31T13:25:29Z","title_canon_sha256":"e5c04cef53c8af8f13df859234d1c15f10b19ef8cbf635c60a7d32fdb4e208ac"},"schema_version":"1.0","source":{"id":"1801.10442","kind":"arxiv","version":1}},"canonical_sha256":"80c63448a612174c0c1bd7c2fa31a6da11729ca16d4cc3994ce5e3eeb0a6a6cd","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"80c63448a612174c0c1bd7c2fa31a6da11729ca16d4cc3994ce5e3eeb0a6a6cd","first_computed_at":"2026-05-18T00:24:40.806910Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:24:40.806910Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"ycLAoXvRFlidGaT/ZZgehHRApKUqI46HcBxnsahnJbY7YcpBmNay7YLnITZi5WUG/ESQpE9QmihaOvxW3NSzDg==","signature_status":"signed_v1","signed_at":"2026-05-18T00:24:40.807666Z","signed_message":"canonical_sha256_bytes"},"source_id":"1801.10442","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:0ddc1f51201915974b14b98e22d9ee5078656d0d5f25ef5708e083e61b875e9e","sha256:3f1302aa34b74589cb9d565faf5f2ddc598b03acd84fcf41de4e63ed2b4ac25a"],"state_sha256":"7fcd11f956ae7dd842610aaa93a25746c5723ea88c7877ae530559682a381b8c"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"xC964e7nA4W24BjL80+4b6WPE/MG7qmMhxbdHxJgYUT+ImRMh597kSc4m2lIgZwdhduD1QnHGzWpDfhNIRmMAA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-31T16:52:40.534332Z","bundle_sha256":"c898811cde7184f0b0ad2b703f0ea5f04e8810d6b5e2a6be3c435554266c7a17"}}