Triple

T23530102
Position Surface form Disambiguated ID Type / Status
Subject Primrose Everdeen E576539 entity
Predicate trainingIn P153131 FINISHED
Object medical care in District 13 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 care in District 13 | Statement: [Primrose Everdeen, trainingIn, medical care in District 13]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: trainingIn
Context triple: [Primrose Everdeen, trainingIn, medical care in District 13]
  • A. training
    Indicates that one entity is teaching, coaching, or otherwise helping another entity acquire or improve a skill, behavior, or capability.
  • B. trainingUnder
    Indicates that one entity is receiving instruction, guidance, or mentorship from another, typically in a subordinate or apprentice-like capacity.
  • C. trainingUse
    Indicates that something is used for training purposes, such as preparing, educating, or improving the skills or performance of an entity.
  • D. trainingComponent
    Indicates that one entity functions as a training-related part, module, or element within a larger training process or system involving another entity.
  • E. providesTrainingFor
    Indicates that one entity delivers or conducts training activities intended to develop the skills or knowledge of another entity.
  • F. None of above. chosen

Provenance (4 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_69e245f5a8848190a2ba42e271c6c31f completed April 17, 2026, 2:38 p.m.
NER Named-entity recognition batch_69f1ac7759e88190aea55c65e24c081f completed April 29, 2026, 7 a.m.
PD Predicate disambiguation batch_69f1189d75b48190a1c01928a993c9fb completed April 28, 2026, 8:29 p.m.
PDg Predicate description generation batch_69f12760784c8190aaeff002ef31febe completed April 28, 2026, 9:32 p.m.
Created at: April 17, 2026, 6:09 p.m.