Triple

T3830344
Position Surface form Disambiguated ID Type / Status
Subject Office of Special Masters of the U.S. Court of Federal Claims E90994 entity
Predicate compensationType P14176 FINISHED
Object medical 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: medical expenses | Statement: [Office of Special Masters of the U.S. Court of Federal Claims, compensationType, medical expenses]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: compensationType
Context triple: [Office of Special Masters of the U.S. Court of Federal Claims, compensationType, medical expenses]
  • A. compensationCategory chosen
    Indicates the type or classification of compensation associated with an entity, such as how or in what form payment or remuneration is provided.
  • B. salaryType
    Indicates the classification or structure of compensation associated with an entity, such as whether pay is salaried, hourly, commission-based, or another type.
  • C. compensationPolicy
    Indicates the rules or guidelines that govern how compensation (such as salary, bonuses, or benefits) is determined and provided.
  • D. compensated
    Indicates that one entity provides payment or some form of recompense to another entity in return for goods, services, or loss incurred.
  • E. typeOfIncentive
    Indicates the specific kind or category of incentive associated with an entity or action.
  • 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_69aed960b538819096561c8ed448dec9 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aeeb8459f881908a2c91bb07e381ef completed March 9, 2026, 3:47 p.m.
PD Predicate disambiguation batch_69aee74c2e04819094b94b3c0bac1806 completed March 9, 2026, 3:29 p.m.
Created at: March 9, 2026, 3:17 p.m.