Triple

T29684044
Position Surface form Disambiguated ID Type / Status
Subject State of Good Repair Grants E751034 entity
Predicate doesNotFund P25443 FINISHED
Object operating expenses 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: operating expenses | Statement: [State of Good Repair Grants, doesNotFund, operating expenses]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: doesNotFund
Context triple: [State of Good Repair Grants, doesNotFund, operating expenses]
  • A. notFundedBy chosen
    Indicates that one entity does not receive financial support, backing, or funding from another entity.
  • B. doesNot
    Indicates that a specified entity lacks, refrains from, or fails to perform a particular action or exhibit a particular property in relation to another entity or context.
  • C. doesNotHave
    Indicates that one entity lacks, is missing, or is not in possession of another entity or attribute.
  • D. doesNotSponsor
    Indicates that one entity does not provide sponsorship or support to another entity.
  • E. doesNotProvideFor
    Indicates that one entity fails or is not responsible for supplying support, resources, or necessary provisions to 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_69f0d625b09481909b0b69aea1e846c8 completed April 28, 2026, 3:45 p.m.
NER Named-entity recognition batch_69f674e06c9481909ed0ea736408f0d7 completed May 2, 2026, 10:04 p.m.
PD Predicate disambiguation batch_69f673c4abec8190bc2379e66f4af0a9 completed May 2, 2026, 9:59 p.m.
Created at: April 28, 2026, 7:12 p.m.