{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2017:XV4LVU7YO4R5ZH7ACHK2GIBN6Z","short_pith_number":"pith:XV4LVU7Y","canonical_record":{"source":{"id":"1707.05308","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2017-07-14T19:01:15Z","cross_cats_sorted":[],"title_canon_sha256":"3861d2e903e48f27ff44b3b224d614ac0d0b8d053c5b37a0156bdede252de56a","abstract_canon_sha256":"eae8b86672f8e0f4fd51987ce7ef9d0eda9a94b8cffda2f3774bb9ab85aeeac8"},"schema_version":"1.0"},"canonical_sha256":"bd78bad3f87723dc9fe011d5a3202df6789bbaa7eeee45ac11259c3a7370063b","source":{"kind":"arxiv","id":"1707.05308","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1707.05308","created_at":"2026-05-18T00:40:02Z"},{"alias_kind":"arxiv_version","alias_value":"1707.05308v1","created_at":"2026-05-18T00:40:02Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1707.05308","created_at":"2026-05-18T00:40:02Z"},{"alias_kind":"pith_short_12","alias_value":"XV4LVU7YO4R5","created_at":"2026-05-18T12:31:56Z"},{"alias_kind":"pith_short_16","alias_value":"XV4LVU7YO4R5ZH7A","created_at":"2026-05-18T12:31:56Z"},{"alias_kind":"pith_short_8","alias_value":"XV4LVU7Y","created_at":"2026-05-18T12:31:56Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2017:XV4LVU7YO4R5ZH7ACHK2GIBN6Z","target":"record","payload":{"canonical_record":{"source":{"id":"1707.05308","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2017-07-14T19:01:15Z","cross_cats_sorted":[],"title_canon_sha256":"3861d2e903e48f27ff44b3b224d614ac0d0b8d053c5b37a0156bdede252de56a","abstract_canon_sha256":"eae8b86672f8e0f4fd51987ce7ef9d0eda9a94b8cffda2f3774bb9ab85aeeac8"},"schema_version":"1.0"},"canonical_sha256":"bd78bad3f87723dc9fe011d5a3202df6789bbaa7eeee45ac11259c3a7370063b","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:40:02.655151Z","signature_b64":"c9zM8NUFvtLYhzzBawkmTMQJ2wingkiLKprJMt8fPtqdErRVANOBEDA1m3DTLUi1TkDNJedaG50QDrE0bQ+kCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"bd78bad3f87723dc9fe011d5a3202df6789bbaa7eeee45ac11259c3a7370063b","last_reissued_at":"2026-05-18T00:40:02.654698Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:40:02.654698Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1707.05308","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":"2026-05-18T00:40:02Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"GHGP63AINOIrWQR6Gm3a35OqgU+S3LoUWibFav22rE0MwwhQSXYDLYjzh454HLiFYsQS1Ia6atHd6BCyuxMhBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-06T15:27:34.324092Z"},"content_sha256":"04b48c64b85f8c441bfcf4c73be1eaf34079593cf331831fc2a3da2a33f91f51","schema_version":"1.0","event_id":"sha256:04b48c64b85f8c441bfcf4c73be1eaf34079593cf331831fc2a3da2a33f91f51"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2017:XV4LVU7YO4R5ZH7ACHK2GIBN6Z","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Knowledge will Propel Machine Understanding of Content: Extrapolating from Current Examples","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.AI","authors_text":"Amit Sheth, Krishnaprasad Thirunarayan, Sanjaya Wijeratne, Sujan Perera","submitted_at":"2017-07-14T19:01:15Z","abstract_excerpt":"Machine Learning has been a big success story during the AI resurgence. One particular stand out success relates to learning from a massive amount of data. In spite of early assertions of the unreasonable effectiveness of data, there is increasing recognition for utilizing knowledge whenever it is available or can be created purposefully. In this paper, we discuss the indispensable role of knowledge for deeper understanding of content where (i) large amounts of training data are unavailable, (ii) the objects to be recognized are complex, (e.g., implicit entities and highly subjective content),"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1707.05308","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":"2026-05-18T00:40:02Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"X88zK7PdstcxnP+hnxGMt8eqUO7rZWNRVdfDfGWuA+WiQOjtWIAJ1dqKOYsxoSfAAywyjxBuaqB0vwhLEcBgBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-06T15:27:34.324768Z"},"content_sha256":"872f9391874e88bc7cf7235d67ed0c50721c9a07cbae40b4a958d191e7ee29eb","schema_version":"1.0","event_id":"sha256:872f9391874e88bc7cf7235d67ed0c50721c9a07cbae40b4a958d191e7ee29eb"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/XV4LVU7YO4R5ZH7ACHK2GIBN6Z/bundle.json","state_url":"https://pith.science/pith/XV4LVU7YO4R5ZH7ACHK2GIBN6Z/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/XV4LVU7YO4R5ZH7ACHK2GIBN6Z/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":"2026-06-06T15:27:34Z","links":{"resolver":"https://pith.science/pith/XV4LVU7YO4R5ZH7ACHK2GIBN6Z","bundle":"https://pith.science/pith/XV4LVU7YO4R5ZH7ACHK2GIBN6Z/bundle.json","state":"https://pith.science/pith/XV4LVU7YO4R5ZH7ACHK2GIBN6Z/state.json","well_known_bundle":"https://pith.science/.well-known/pith/XV4LVU7YO4R5ZH7ACHK2GIBN6Z/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:XV4LVU7YO4R5ZH7ACHK2GIBN6Z","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":"eae8b86672f8e0f4fd51987ce7ef9d0eda9a94b8cffda2f3774bb9ab85aeeac8","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2017-07-14T19:01:15Z","title_canon_sha256":"3861d2e903e48f27ff44b3b224d614ac0d0b8d053c5b37a0156bdede252de56a"},"schema_version":"1.0","source":{"id":"1707.05308","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1707.05308","created_at":"2026-05-18T00:40:02Z"},{"alias_kind":"arxiv_version","alias_value":"1707.05308v1","created_at":"2026-05-18T00:40:02Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1707.05308","created_at":"2026-05-18T00:40:02Z"},{"alias_kind":"pith_short_12","alias_value":"XV4LVU7YO4R5","created_at":"2026-05-18T12:31:56Z"},{"alias_kind":"pith_short_16","alias_value":"XV4LVU7YO4R5ZH7A","created_at":"2026-05-18T12:31:56Z"},{"alias_kind":"pith_short_8","alias_value":"XV4LVU7Y","created_at":"2026-05-18T12:31:56Z"}],"graph_snapshots":[{"event_id":"sha256:872f9391874e88bc7cf7235d67ed0c50721c9a07cbae40b4a958d191e7ee29eb","target":"graph","created_at":"2026-05-18T00:40:02Z","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":"Machine Learning has been a big success story during the AI resurgence. One particular stand out success relates to learning from a massive amount of data. In spite of early assertions of the unreasonable effectiveness of data, there is increasing recognition for utilizing knowledge whenever it is available or can be created purposefully. In this paper, we discuss the indispensable role of knowledge for deeper understanding of content where (i) large amounts of training data are unavailable, (ii) the objects to be recognized are complex, (e.g., implicit entities and highly subjective content),","authors_text":"Amit Sheth, Krishnaprasad Thirunarayan, Sanjaya Wijeratne, Sujan Perera","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2017-07-14T19:01:15Z","title":"Knowledge will Propel Machine Understanding of Content: Extrapolating from Current Examples"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1707.05308","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":"sha256:04b48c64b85f8c441bfcf4c73be1eaf34079593cf331831fc2a3da2a33f91f51","target":"record","created_at":"2026-05-18T00:40:02Z","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":"eae8b86672f8e0f4fd51987ce7ef9d0eda9a94b8cffda2f3774bb9ab85aeeac8","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2017-07-14T19:01:15Z","title_canon_sha256":"3861d2e903e48f27ff44b3b224d614ac0d0b8d053c5b37a0156bdede252de56a"},"schema_version":"1.0","source":{"id":"1707.05308","kind":"arxiv","version":1}},"canonical_sha256":"bd78bad3f87723dc9fe011d5a3202df6789bbaa7eeee45ac11259c3a7370063b","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"bd78bad3f87723dc9fe011d5a3202df6789bbaa7eeee45ac11259c3a7370063b","first_computed_at":"2026-05-18T00:40:02.654698Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:40:02.654698Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"c9zM8NUFvtLYhzzBawkmTMQJ2wingkiLKprJMt8fPtqdErRVANOBEDA1m3DTLUi1TkDNJedaG50QDrE0bQ+kCQ==","signature_status":"signed_v1","signed_at":"2026-05-18T00:40:02.655151Z","signed_message":"canonical_sha256_bytes"},"source_id":"1707.05308","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:04b48c64b85f8c441bfcf4c73be1eaf34079593cf331831fc2a3da2a33f91f51","sha256:872f9391874e88bc7cf7235d67ed0c50721c9a07cbae40b4a958d191e7ee29eb"],"state_sha256":"9eb54ee33628092e47697698c9542100fd019b5b2a838bf6a643cbc6ced9deb5"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"kcdaQYmxN4pqq3Cxw6xNHXVJk1kFkHSkTFhueB794JHoT7X0b7rJgTVRFfdpcij1rdV4N8mNUErbb/OYeHfeDg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-06T15:27:34.328278Z","bundle_sha256":"a8010d3e3aa739cc34ea7cdb5a2fa2c03c5222440f863063d604da9cd2c5e0b4"}}