Triple

T2277000
Position Surface form Disambiguated ID Type / Status
Subject United States transportation system E50792 entity
Predicate keyPolicyArea P7262 FINISHED
Object federal transportation policy LITERAL FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: federal transportation policy | Statement: [United States transportation system, keyPolicyArea, federal transportation policy]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: keyPolicyArea
Context triple: [United States transportation system, keyPolicyArea, federal transportation policy]
  • A. keyIssueArea
    Indicates that something is a primary topic, domain, or field that is central or especially important within a broader context or discussion.
  • B. commonPolicyArea
    Indicates that two entities share the same policy domain, topic, or area of regulatory or legislative focus.
  • C. isPartOfPolicyArea
    Indicates that one policy, topic, or issue belongs to, falls under, or is categorized within a broader policy area or domain.
  • D. hasPolicyArea chosen
    Indicates that an entity (such as a policy, program, or initiative) is associated with or pertains to a specific policy area or domain.
  • E. coversPolicyArea
    Indicates that a policy, document, or initiative includes or addresses a particular policy area or topic within its scope.
  • F. None of above.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69a88b05910c8190a9a2b1ff230c85f9 completed March 4, 2026, 7:41 p.m.
NER Named-entity recognition batch_69abc1ee22988190b7fa28b0b62e8668 completed March 7, 2026, 6:13 a.m.
PD Predicate disambiguation batch_69abbdb9aa3c819088d0316c5269a1c2 completed March 7, 2026, 5:55 a.m.
Created at: March 4, 2026, 7:48 p.m.