{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2017:BPRUEDOAOCOILAUY2KJJSKCPYU","short_pith_number":"pith:BPRUEDOA","canonical_record":{"source":{"id":"1707.05967","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2017-07-19T07:51:05Z","cross_cats_sorted":[],"title_canon_sha256":"8eb6f7602d56807c8e5d06a250bfc4174081b7f4c1d4e254374b2c0c9f51f57e","abstract_canon_sha256":"56d65b9b505ec0fd8eb63c34e8a25557e25317556a001bfd8158ca29255504b2"},"schema_version":"1.0"},"canonical_sha256":"0be3420dc0709c858298d29299284fc50b6af0108b7ff1379ba0711b574c1d65","source":{"kind":"arxiv","id":"1707.05967","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1707.05967","created_at":"2026-05-18T00:39:25Z"},{"alias_kind":"arxiv_version","alias_value":"1707.05967v2","created_at":"2026-05-18T00:39:25Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1707.05967","created_at":"2026-05-18T00:39:25Z"},{"alias_kind":"pith_short_12","alias_value":"BPRUEDOAOCOI","created_at":"2026-05-18T12:31:08Z"},{"alias_kind":"pith_short_16","alias_value":"BPRUEDOAOCOILAUY","created_at":"2026-05-18T12:31:08Z"},{"alias_kind":"pith_short_8","alias_value":"BPRUEDOA","created_at":"2026-05-18T12:31:08Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2017:BPRUEDOAOCOILAUY2KJJSKCPYU","target":"record","payload":{"canonical_record":{"source":{"id":"1707.05967","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2017-07-19T07:51:05Z","cross_cats_sorted":[],"title_canon_sha256":"8eb6f7602d56807c8e5d06a250bfc4174081b7f4c1d4e254374b2c0c9f51f57e","abstract_canon_sha256":"56d65b9b505ec0fd8eb63c34e8a25557e25317556a001bfd8158ca29255504b2"},"schema_version":"1.0"},"canonical_sha256":"0be3420dc0709c858298d29299284fc50b6af0108b7ff1379ba0711b574c1d65","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:39:25.356015Z","signature_b64":"DAId+7NyG/0q8zn+B2Xzq/K9oglBetTMcQkMXTEYYk76mF/jfmutYf77Amhg7fxhFz+2fRvXJDJWBzLLRIKbBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"0be3420dc0709c858298d29299284fc50b6af0108b7ff1379ba0711b574c1d65","last_reissued_at":"2026-05-18T00:39:25.355398Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:39:25.355398Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1707.05967","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":"2026-05-18T00:39:25Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"N/VhwQwAejrlEX9jJG7JAB7JTC6AwjjGcvYcixS1MFY8uw9uPQUVDSyeJ+vJr0714ZucQv80SZ6oRLdcBPBXAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-01T15:33:05.056573Z"},"content_sha256":"ba8d2ab35c847f2ba8950bb04e18b0b7f388fee68a97fdfbedd6d41618a29167","schema_version":"1.0","event_id":"sha256:ba8d2ab35c847f2ba8950bb04e18b0b7f388fee68a97fdfbedd6d41618a29167"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2017:BPRUEDOAOCOILAUY2KJJSKCPYU","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Measuring Thematic Fit with Distributional Feature Overlap","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Alessandro Lenci, Emmanuele Chersoni, Enrico Santus, Philippe Blache","submitted_at":"2017-07-19T07:51:05Z","abstract_excerpt":"In this paper, we introduce a new distributional method for modeling predicate-argument thematic fit judgments. We use a syntax-based DSM to build a prototypical representation of verb-specific roles: for every verb, we extract the most salient second order contexts for each of its roles (i.e. the most salient dimensions of typical role fillers), and then we compute thematic fit as a weighted overlap between the top features of candidate fillers and role prototypes. Our experiments show that our method consistently outperforms a baseline re-implementing a state-of-the-art system, and achieves "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1707.05967","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":""},"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":"2026-05-18T00:39:25Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"cqtEoUaRnDQvlQTPkUdO6fQJmV04mUsujpfZLkJaZ+aosyWw65CAw/AZCkS6GoVJdWeQsUCLU3AG48vOu2tfDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-01T15:33:05.056938Z"},"content_sha256":"7a4c5b4a8ce1a0fec79acd2706b1e6bdc516528bb57494ef14e522a23df10e82","schema_version":"1.0","event_id":"sha256:7a4c5b4a8ce1a0fec79acd2706b1e6bdc516528bb57494ef14e522a23df10e82"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/BPRUEDOAOCOILAUY2KJJSKCPYU/bundle.json","state_url":"https://pith.science/pith/BPRUEDOAOCOILAUY2KJJSKCPYU/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/BPRUEDOAOCOILAUY2KJJSKCPYU/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":"2026-06-01T15:33:05Z","links":{"resolver":"https://pith.science/pith/BPRUEDOAOCOILAUY2KJJSKCPYU","bundle":"https://pith.science/pith/BPRUEDOAOCOILAUY2KJJSKCPYU/bundle.json","state":"https://pith.science/pith/BPRUEDOAOCOILAUY2KJJSKCPYU/state.json","well_known_bundle":"https://pith.science/.well-known/pith/BPRUEDOAOCOILAUY2KJJSKCPYU/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:BPRUEDOAOCOILAUY2KJJSKCPYU","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":"56d65b9b505ec0fd8eb63c34e8a25557e25317556a001bfd8158ca29255504b2","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2017-07-19T07:51:05Z","title_canon_sha256":"8eb6f7602d56807c8e5d06a250bfc4174081b7f4c1d4e254374b2c0c9f51f57e"},"schema_version":"1.0","source":{"id":"1707.05967","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1707.05967","created_at":"2026-05-18T00:39:25Z"},{"alias_kind":"arxiv_version","alias_value":"1707.05967v2","created_at":"2026-05-18T00:39:25Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1707.05967","created_at":"2026-05-18T00:39:25Z"},{"alias_kind":"pith_short_12","alias_value":"BPRUEDOAOCOI","created_at":"2026-05-18T12:31:08Z"},{"alias_kind":"pith_short_16","alias_value":"BPRUEDOAOCOILAUY","created_at":"2026-05-18T12:31:08Z"},{"alias_kind":"pith_short_8","alias_value":"BPRUEDOA","created_at":"2026-05-18T12:31:08Z"}],"graph_snapshots":[{"event_id":"sha256:7a4c5b4a8ce1a0fec79acd2706b1e6bdc516528bb57494ef14e522a23df10e82","target":"graph","created_at":"2026-05-18T00:39:25Z","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":"In this paper, we introduce a new distributional method for modeling predicate-argument thematic fit judgments. We use a syntax-based DSM to build a prototypical representation of verb-specific roles: for every verb, we extract the most salient second order contexts for each of its roles (i.e. the most salient dimensions of typical role fillers), and then we compute thematic fit as a weighted overlap between the top features of candidate fillers and role prototypes. Our experiments show that our method consistently outperforms a baseline re-implementing a state-of-the-art system, and achieves ","authors_text":"Alessandro Lenci, Emmanuele Chersoni, Enrico Santus, Philippe Blache","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2017-07-19T07:51:05Z","title":"Measuring Thematic Fit with Distributional Feature Overlap"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1707.05967","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:ba8d2ab35c847f2ba8950bb04e18b0b7f388fee68a97fdfbedd6d41618a29167","target":"record","created_at":"2026-05-18T00:39:25Z","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":"56d65b9b505ec0fd8eb63c34e8a25557e25317556a001bfd8158ca29255504b2","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2017-07-19T07:51:05Z","title_canon_sha256":"8eb6f7602d56807c8e5d06a250bfc4174081b7f4c1d4e254374b2c0c9f51f57e"},"schema_version":"1.0","source":{"id":"1707.05967","kind":"arxiv","version":2}},"canonical_sha256":"0be3420dc0709c858298d29299284fc50b6af0108b7ff1379ba0711b574c1d65","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"0be3420dc0709c858298d29299284fc50b6af0108b7ff1379ba0711b574c1d65","first_computed_at":"2026-05-18T00:39:25.355398Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:39:25.355398Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"DAId+7NyG/0q8zn+B2Xzq/K9oglBetTMcQkMXTEYYk76mF/jfmutYf77Amhg7fxhFz+2fRvXJDJWBzLLRIKbBA==","signature_status":"signed_v1","signed_at":"2026-05-18T00:39:25.356015Z","signed_message":"canonical_sha256_bytes"},"source_id":"1707.05967","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:ba8d2ab35c847f2ba8950bb04e18b0b7f388fee68a97fdfbedd6d41618a29167","sha256:7a4c5b4a8ce1a0fec79acd2706b1e6bdc516528bb57494ef14e522a23df10e82"],"state_sha256":"43358a27783b6e6a1ba891b22e662170105809898881476f29469d6fda2d8c05"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"1yfox1ObQnLhB6ThRpFuHjRZLKjxh4pgYCpzm++bAgLCNFq1/UjWoYiAjUfdTNjNL/H4iFSoxkK+dka4/C2NBQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-01T15:33:05.058902Z","bundle_sha256":"42a4c2275aa11185c0f47207ebef91afb974b58e260b69aa7e7bfa5b5b7daea1"}}