{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2017:GTNISEEORYDEUCH4SFLNZAWP3V","short_pith_number":"pith:GTNISEEO","canonical_record":{"source":{"id":"1709.05743","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IR","submitted_at":"2017-09-18T02:09:08Z","cross_cats_sorted":["cs.CL"],"title_canon_sha256":"1b905c8ac48f01d671ba970b62a67a8124b93102b38dffefd9bb9f8dc6640050","abstract_canon_sha256":"554784ea3b1dc7f75c3ee76f9b2dcbbdcb7ca58963e2608ffa92a9f14b02460a"},"schema_version":"1.0"},"canonical_sha256":"34da89108e8e064a08fc9156dc82cfdd5c53fc89b93e3c39a5734b9e1acf72cd","source":{"kind":"arxiv","id":"1709.05743","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1709.05743","created_at":"2026-05-18T00:34:59Z"},{"alias_kind":"arxiv_version","alias_value":"1709.05743v1","created_at":"2026-05-18T00:34:59Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1709.05743","created_at":"2026-05-18T00:34:59Z"},{"alias_kind":"pith_short_12","alias_value":"GTNISEEORYDE","created_at":"2026-05-18T12:31:18Z"},{"alias_kind":"pith_short_16","alias_value":"GTNISEEORYDEUCH4","created_at":"2026-05-18T12:31:18Z"},{"alias_kind":"pith_short_8","alias_value":"GTNISEEO","created_at":"2026-05-18T12:31:18Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2017:GTNISEEORYDEUCH4SFLNZAWP3V","target":"record","payload":{"canonical_record":{"source":{"id":"1709.05743","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IR","submitted_at":"2017-09-18T02:09:08Z","cross_cats_sorted":["cs.CL"],"title_canon_sha256":"1b905c8ac48f01d671ba970b62a67a8124b93102b38dffefd9bb9f8dc6640050","abstract_canon_sha256":"554784ea3b1dc7f75c3ee76f9b2dcbbdcb7ca58963e2608ffa92a9f14b02460a"},"schema_version":"1.0"},"canonical_sha256":"34da89108e8e064a08fc9156dc82cfdd5c53fc89b93e3c39a5734b9e1acf72cd","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:34:59.576944Z","signature_b64":"kScbJcL5w6/ZEKvl5j2zW19cw/ISWsvNdJwyY27jOIf68AAUnECj6OsAAgcODwAByFTXOLOC55I/SVmmK41bCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"34da89108e8e064a08fc9156dc82cfdd5c53fc89b93e3c39a5734b9e1acf72cd","last_reissued_at":"2026-05-18T00:34:59.576257Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:34:59.576257Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1709.05743","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":"2026-05-18T00:34:59Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"s41JZ0a5h1mcU1tRFv2ZKcXGQLeBtM1WiXk2LgmKuZio20XmQ1tnZHUKtZGFXeEFWtSzLdZ9+eSpRhXZPEKoCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-26T10:03:05.420008Z"},"content_sha256":"db5d0e3f3e0479e19fdc1606a54fb7d2af011b75e2254da327aa6b6a2892c64d","schema_version":"1.0","event_id":"sha256:db5d0e3f3e0479e19fdc1606a54fb7d2af011b75e2254da327aa6b6a2892c64d"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2017:GTNISEEORYDEUCH4SFLNZAWP3V","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Towards Building a Knowledge Base of Monetary Transactions from a News Collection","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CL"],"primary_cat":"cs.IR","authors_text":"Jan R. Benetka, Kjetil N{\\o}rv{\\aa}g, Krisztian Balog","submitted_at":"2017-09-18T02:09:08Z","abstract_excerpt":"We address the problem of extracting structured representations of economic events from a large corpus of news articles, using a combination of natural language processing and machine learning techniques. The developed techniques allow for semi-automatic population of a financial knowledge base, which, in turn, may be used to support a range of data mining and exploration tasks. The key challenge we face in this domain is that the same event is often reported multiple times, with varying correctness of details. We address this challenge by first collecting all information pertinent to a given "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1709.05743","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":"2026-05-18T00:34:59Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"PiqveiszNavFo6DUJdYm3zzz27GmZOqxbBh2EjN6dHnxV/zn3a897eLso7cwBkRQHYAO6QFsMH9EmlXGLbO0DQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-26T10:03:05.420718Z"},"content_sha256":"8bd5f0be585f7c2d8dbd808dfc2c8f043413714c2ab3140130b5d88fba9c3ea2","schema_version":"1.0","event_id":"sha256:8bd5f0be585f7c2d8dbd808dfc2c8f043413714c2ab3140130b5d88fba9c3ea2"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/GTNISEEORYDEUCH4SFLNZAWP3V/bundle.json","state_url":"https://pith.science/pith/GTNISEEORYDEUCH4SFLNZAWP3V/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/GTNISEEORYDEUCH4SFLNZAWP3V/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":"2026-05-26T10:03:05Z","links":{"resolver":"https://pith.science/pith/GTNISEEORYDEUCH4SFLNZAWP3V","bundle":"https://pith.science/pith/GTNISEEORYDEUCH4SFLNZAWP3V/bundle.json","state":"https://pith.science/pith/GTNISEEORYDEUCH4SFLNZAWP3V/state.json","well_known_bundle":"https://pith.science/.well-known/pith/GTNISEEORYDEUCH4SFLNZAWP3V/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:GTNISEEORYDEUCH4SFLNZAWP3V","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":"554784ea3b1dc7f75c3ee76f9b2dcbbdcb7ca58963e2608ffa92a9f14b02460a","cross_cats_sorted":["cs.CL"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IR","submitted_at":"2017-09-18T02:09:08Z","title_canon_sha256":"1b905c8ac48f01d671ba970b62a67a8124b93102b38dffefd9bb9f8dc6640050"},"schema_version":"1.0","source":{"id":"1709.05743","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1709.05743","created_at":"2026-05-18T00:34:59Z"},{"alias_kind":"arxiv_version","alias_value":"1709.05743v1","created_at":"2026-05-18T00:34:59Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1709.05743","created_at":"2026-05-18T00:34:59Z"},{"alias_kind":"pith_short_12","alias_value":"GTNISEEORYDE","created_at":"2026-05-18T12:31:18Z"},{"alias_kind":"pith_short_16","alias_value":"GTNISEEORYDEUCH4","created_at":"2026-05-18T12:31:18Z"},{"alias_kind":"pith_short_8","alias_value":"GTNISEEO","created_at":"2026-05-18T12:31:18Z"}],"graph_snapshots":[{"event_id":"sha256:8bd5f0be585f7c2d8dbd808dfc2c8f043413714c2ab3140130b5d88fba9c3ea2","target":"graph","created_at":"2026-05-18T00:34:59Z","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 address the problem of extracting structured representations of economic events from a large corpus of news articles, using a combination of natural language processing and machine learning techniques. The developed techniques allow for semi-automatic population of a financial knowledge base, which, in turn, may be used to support a range of data mining and exploration tasks. The key challenge we face in this domain is that the same event is often reported multiple times, with varying correctness of details. We address this challenge by first collecting all information pertinent to a given ","authors_text":"Jan R. Benetka, Kjetil N{\\o}rv{\\aa}g, Krisztian Balog","cross_cats":["cs.CL"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IR","submitted_at":"2017-09-18T02:09:08Z","title":"Towards Building a Knowledge Base of Monetary Transactions from a News Collection"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1709.05743","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:db5d0e3f3e0479e19fdc1606a54fb7d2af011b75e2254da327aa6b6a2892c64d","target":"record","created_at":"2026-05-18T00:34:59Z","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":"554784ea3b1dc7f75c3ee76f9b2dcbbdcb7ca58963e2608ffa92a9f14b02460a","cross_cats_sorted":["cs.CL"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IR","submitted_at":"2017-09-18T02:09:08Z","title_canon_sha256":"1b905c8ac48f01d671ba970b62a67a8124b93102b38dffefd9bb9f8dc6640050"},"schema_version":"1.0","source":{"id":"1709.05743","kind":"arxiv","version":1}},"canonical_sha256":"34da89108e8e064a08fc9156dc82cfdd5c53fc89b93e3c39a5734b9e1acf72cd","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"34da89108e8e064a08fc9156dc82cfdd5c53fc89b93e3c39a5734b9e1acf72cd","first_computed_at":"2026-05-18T00:34:59.576257Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:34:59.576257Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"kScbJcL5w6/ZEKvl5j2zW19cw/ISWsvNdJwyY27jOIf68AAUnECj6OsAAgcODwAByFTXOLOC55I/SVmmK41bCQ==","signature_status":"signed_v1","signed_at":"2026-05-18T00:34:59.576944Z","signed_message":"canonical_sha256_bytes"},"source_id":"1709.05743","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:db5d0e3f3e0479e19fdc1606a54fb7d2af011b75e2254da327aa6b6a2892c64d","sha256:8bd5f0be585f7c2d8dbd808dfc2c8f043413714c2ab3140130b5d88fba9c3ea2"],"state_sha256":"7b2da79cdcf5c6544fc9027bc5d799800668a02a4c450f15ee8e2cca66ce9ddd"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"C+HM/v+MCFXyLfcBbQUjJY1QziOdOFmNsMi2Yf64EvX35/qEDz+woDdRzESDKmTgfkKfv2GC4fQ1qU36gajdBg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-26T10:03:05.424117Z","bundle_sha256":"50f1307763b3c46f1a2eba563c158504d6346791695155c4f5e020cf67475fe1"}}