Triple

T20562525
Position Surface form Disambiguated ID Type / Status
Subject Strong Vincent E504877 entity
Predicate woundEvent P28646 FINISHED
Object defense of Little Round Top 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: defense of Little Round Top | Statement: [Strong Vincent, woundEvent, defense of Little Round Top]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: woundEvent
Context triple: [Strong Vincent, woundEvent, defense of Little Round Top]
  • A. woundedAt
    Indicates that an entity was injured or harmed at a specific place or during a particular event.
  • B. woundLocation
    Indicates the specific anatomical site on an entity’s body where a wound is present or occurred.
  • C. wasWoundedIn chosen
    Indicates that an entity sustained an injury as a result of a specified event, situation, or conflict.
  • D. formationEvent
    Indicates the event or process through which something comes into existence, is created, or is initially established.
  • E. actedDespiteWounds
    Indicates that an entity performed an action or fulfilled a role even though it was wounded or injured at the time.
  • 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_69e0b4b6587c8190aee63dc7cff244ea completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e6a79f906c819081163de9649ccb17 completed April 20, 2026, 10:24 p.m.
PD Predicate disambiguation batch_69e59ff0116c8190a163ff28ed01430a completed April 20, 2026, 3:39 a.m.
Created at: April 16, 2026, 11:39 a.m.