{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:5MZYIHKKLTNV4Q2FE736IJFC5O","short_pith_number":"pith:5MZYIHKK","canonical_record":{"source":{"id":"1908.06049","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DB","submitted_at":"2019-08-16T16:30:05Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"0f90a1bf7dbb2623bb3191d47af251f9c4bc6b09e487fcfe4d0597f6e0148863","abstract_canon_sha256":"b27e914e23a04f60e0e155d4a1d7624b65eeb0d8f512c275b3c566eca10a64e5"},"schema_version":"1.0"},"canonical_sha256":"eb33841d4a5cdb5e434527f7e424a2eb819caa9c46c2a0607f7c414d8c41492a","source":{"kind":"arxiv","id":"1908.06049","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1908.06049","created_at":"2026-07-05T00:52:47Z"},{"alias_kind":"arxiv_version","alias_value":"1908.06049v2","created_at":"2026-07-05T00:52:47Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1908.06049","created_at":"2026-07-05T00:52:47Z"},{"alias_kind":"pith_short_12","alias_value":"5MZYIHKKLTNV","created_at":"2026-07-05T00:52:47Z"},{"alias_kind":"pith_short_16","alias_value":"5MZYIHKKLTNV4Q2F","created_at":"2026-07-05T00:52:47Z"},{"alias_kind":"pith_short_8","alias_value":"5MZYIHKK","created_at":"2026-07-05T00:52:47Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:5MZYIHKKLTNV4Q2FE736IJFC5O","target":"record","payload":{"canonical_record":{"source":{"id":"1908.06049","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DB","submitted_at":"2019-08-16T16:30:05Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"0f90a1bf7dbb2623bb3191d47af251f9c4bc6b09e487fcfe4d0597f6e0148863","abstract_canon_sha256":"b27e914e23a04f60e0e155d4a1d7624b65eeb0d8f512c275b3c566eca10a64e5"},"schema_version":"1.0"},"canonical_sha256":"eb33841d4a5cdb5e434527f7e424a2eb819caa9c46c2a0607f7c414d8c41492a","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T00:52:47.915988Z","signature_b64":"m14UNg1fOaFYNxNPmIq6rXaEo189xKQkdBhGY80w+/EA3QKqC/4G5vVF/T2TiF+3GdTc+fZ8S4haswI+DLbxBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"eb33841d4a5cdb5e434527f7e424a2eb819caa9c46c2a0607f7c414d8c41492a","last_reissued_at":"2026-07-05T00:52:47.915535Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T00:52:47.915535Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1908.06049","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T00:52:47Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"/AAFkGfp2m0Mzn4bRVyQNb3H9/SIh9Xgaqz1xDA08AhR3aJdyvwYaS0dAnj+mLPSCG0cAOegRr/y/P0TN5tcDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-01T12:32:19.350574Z"},"content_sha256":"9aacfe9d06949a30fb0aa3a1cc2a99c5a4ad2c56caea87fbdf54ecbff88b1a83","schema_version":"1.0","event_id":"sha256:9aacfe9d06949a30fb0aa3a1cc2a99c5a4ad2c56caea87fbdf54ecbff88b1a83"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:5MZYIHKKLTNV4Q2FE736IJFC5O","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"ZeroER: Entity Resolution using Zero Labeled Examples","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.DB","authors_text":"Renzhi Wu, Sanya Chaba, Saravanan Thirumuruganathan, Saurabh Sawlani, Xu Chu","submitted_at":"2019-08-16T16:30:05Z","abstract_excerpt":"Entity resolution (ER) refers to the problem of matching records in one or more relations that refer to the same real-world entity. While supervised machine learning (ML) approaches achieve the state-of-the-art results, they require a large amount of labeled examples that are expensive to obtain and often times infeasible. We investigate an important problem that vexes practitioners: is it possible to design an effective algorithm for ER that requires Zero labeled examples, yet can achieve performance comparable to supervised approaches? In this paper, we answer in the affirmative through our "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1908.06049","kind":"arxiv","version":2},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/1908.06049/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"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":"2026-07-05T00:52:47Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"HvodPHBGKMheCmFEvjZhhZnxIpFrAAFW3zu+vU8oOLMPXpLJhG8DSxVx0yHCPx3l+OyzfCrMMGN14ciTjwuBCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-01T12:32:19.351045Z"},"content_sha256":"4a30021fe51a36ecc47dc271953509b3d754ef955f8fe23cb4ec6b5a6978039f","schema_version":"1.0","event_id":"sha256:4a30021fe51a36ecc47dc271953509b3d754ef955f8fe23cb4ec6b5a6978039f"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/5MZYIHKKLTNV4Q2FE736IJFC5O/bundle.json","state_url":"https://pith.science/pith/5MZYIHKKLTNV4Q2FE736IJFC5O/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/5MZYIHKKLTNV4Q2FE736IJFC5O/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":"2026-08-01T12:32:19Z","links":{"resolver":"https://pith.science/pith/5MZYIHKKLTNV4Q2FE736IJFC5O","bundle":"https://pith.science/pith/5MZYIHKKLTNV4Q2FE736IJFC5O/bundle.json","state":"https://pith.science/pith/5MZYIHKKLTNV4Q2FE736IJFC5O/state.json","well_known_bundle":"https://pith.science/.well-known/pith/5MZYIHKKLTNV4Q2FE736IJFC5O/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:5MZYIHKKLTNV4Q2FE736IJFC5O","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":"b27e914e23a04f60e0e155d4a1d7624b65eeb0d8f512c275b3c566eca10a64e5","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DB","submitted_at":"2019-08-16T16:30:05Z","title_canon_sha256":"0f90a1bf7dbb2623bb3191d47af251f9c4bc6b09e487fcfe4d0597f6e0148863"},"schema_version":"1.0","source":{"id":"1908.06049","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1908.06049","created_at":"2026-07-05T00:52:47Z"},{"alias_kind":"arxiv_version","alias_value":"1908.06049v2","created_at":"2026-07-05T00:52:47Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1908.06049","created_at":"2026-07-05T00:52:47Z"},{"alias_kind":"pith_short_12","alias_value":"5MZYIHKKLTNV","created_at":"2026-07-05T00:52:47Z"},{"alias_kind":"pith_short_16","alias_value":"5MZYIHKKLTNV4Q2F","created_at":"2026-07-05T00:52:47Z"},{"alias_kind":"pith_short_8","alias_value":"5MZYIHKK","created_at":"2026-07-05T00:52:47Z"}],"graph_snapshots":[{"event_id":"sha256:4a30021fe51a36ecc47dc271953509b3d754ef955f8fe23cb4ec6b5a6978039f","target":"graph","created_at":"2026-07-05T00:52:47Z","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"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/1908.06049/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Entity resolution (ER) refers to the problem of matching records in one or more relations that refer to the same real-world entity. While supervised machine learning (ML) approaches achieve the state-of-the-art results, they require a large amount of labeled examples that are expensive to obtain and often times infeasible. We investigate an important problem that vexes practitioners: is it possible to design an effective algorithm for ER that requires Zero labeled examples, yet can achieve performance comparable to supervised approaches? In this paper, we answer in the affirmative through our ","authors_text":"Renzhi Wu, Sanya Chaba, Saravanan Thirumuruganathan, Saurabh Sawlani, Xu Chu","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DB","submitted_at":"2019-08-16T16:30:05Z","title":"ZeroER: Entity Resolution using Zero Labeled Examples"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1908.06049","kind":"arxiv","version":2},"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":"sha256:9aacfe9d06949a30fb0aa3a1cc2a99c5a4ad2c56caea87fbdf54ecbff88b1a83","target":"record","created_at":"2026-07-05T00:52:47Z","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":"b27e914e23a04f60e0e155d4a1d7624b65eeb0d8f512c275b3c566eca10a64e5","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DB","submitted_at":"2019-08-16T16:30:05Z","title_canon_sha256":"0f90a1bf7dbb2623bb3191d47af251f9c4bc6b09e487fcfe4d0597f6e0148863"},"schema_version":"1.0","source":{"id":"1908.06049","kind":"arxiv","version":2}},"canonical_sha256":"eb33841d4a5cdb5e434527f7e424a2eb819caa9c46c2a0607f7c414d8c41492a","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"eb33841d4a5cdb5e434527f7e424a2eb819caa9c46c2a0607f7c414d8c41492a","first_computed_at":"2026-07-05T00:52:47.915535Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T00:52:47.915535Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"m14UNg1fOaFYNxNPmIq6rXaEo189xKQkdBhGY80w+/EA3QKqC/4G5vVF/T2TiF+3GdTc+fZ8S4haswI+DLbxBQ==","signature_status":"signed_v1","signed_at":"2026-07-05T00:52:47.915988Z","signed_message":"canonical_sha256_bytes"},"source_id":"1908.06049","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:9aacfe9d06949a30fb0aa3a1cc2a99c5a4ad2c56caea87fbdf54ecbff88b1a83","sha256:4a30021fe51a36ecc47dc271953509b3d754ef955f8fe23cb4ec6b5a6978039f"],"state_sha256":"a9cf89d659d3d51027db4af591408ccc928a4c97155dbe9f0e2b1a2b77442439"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"xuds8KMcn4Q8op8wVrGJkTev67a5bbg6/UxvBT08mqrfgngYENglRceoMP2o6BtSMAx6z2Dt9W8Es9hO0lOcDw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-01T12:32:19.354244Z","bundle_sha256":"15f408eb4a112abf6b0192c1cd855f2a5340bad3de3767ab2722484b165e9738"}}