Triple

T11294983
Position Surface form Disambiguated ID Type / Status
Subject STPF E267426 entity
Predicate benefitToGovernment P487 FINISHED
Object access to scientific and technical expertise 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: access to scientific and technical expertise | Statement: [STPF, benefitToGovernment, access to scientific and technical expertise]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: benefitToGovernment
Context triple: [STPF, benefitToGovernment, access to scientific and technical expertise]
  • A. sectorBenefited
    Indicates that a particular sector gains advantage, support, or positive impact from a given action, policy, resource, or entity.
  • B. supportedGovernment
    Indicates that one entity provided assistance, endorsement, or backing to a particular government or governing authority.
  • C. benefitsAre
    Indicates that certain advantages, gains, or positive outcomes are possessed by or accrue to a particular entity or group.
  • D. benefits chosen
    Indicates that one entity gains an advantage, improvement, or positive outcome as a result of another entity or action.
  • E. affectsBenefit
    Indicates that one entity has an influence on, modifies, or determines the benefit or advantage received by another entity.
  • 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_69d6aac993a08190a6f36445ebaf9a43 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e98b149481909f432a6b9ef8bfbb completed April 9, 2026, 6:01 p.m.
PD Predicate disambiguation batch_69d787a6ca2c8190afdc24b61ccd3f8a completed April 9, 2026, 11:04 a.m.
Created at: April 8, 2026, 9:32 p.m.