Triple

T37873322
Position Surface form Disambiguated ID Type / Status
Subject Crossroads E944657 entity
Predicate hasClassTrainers P196068 FINISHED
Object true 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: true | Statement: [Crossroads, hasClassTrainers, true]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasClassTrainers
Context triple: [Crossroads, hasClassTrainers, true]
  • A. hasClassTrainersFor
    Indicates that an entity provides or is associated with trainers responsible for conducting or leading a particular class.
  • B. hasTrainingFor
    Indicates that an entity has received or possesses training that prepares it for performing a specific task, role, or function.
  • C. hasOnScreenTrainer
    Indicates that an entity has a trainer or instructor who appears on screen (e.g., in a video or broadcast) providing guidance or instruction.
  • D. hasTrainingBaseIn
    Indicates that an entity maintains or operates a training base located in a specified place.
  • E. hasTrainingRole
    Indicates that an entity holds or is assigned a specific role within a training or instructional context.
  • 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_69f76eef55d481908ca6660b4b532550 completed May 3, 2026, 3:51 p.m.
NER Named-entity recognition batch_69fe031bc6208190860099aef72d8dcb completed May 8, 2026, 3:36 p.m.
PD Predicate disambiguation batch_69fe014c8b388190b5d4e0cb95ee2be5 completed May 8, 2026, 3:29 p.m.
PDg Predicate description generation batch_69fe031af3248190816da6829aef7bab completed May 8, 2026, 3:36 p.m.
Created at: May 3, 2026, 4:19 p.m.