Triple

T25177219
Position Surface form Disambiguated ID Type / Status
Subject The Thin Red Line E630480 entity
Predicate forceRatio P157526 FINISHED
Object small British infantry force vs larger Russian cavalry force 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: small British infantry force vs larger Russian cavalry force | Statement: [The Thin Red Line, forceRatio, small British infantry force vs larger Russian cavalry force]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: forceRatio
Context triple: [The Thin Red Line, forceRatio, small British infantry force vs larger Russian cavalry force]
  • A. forceRatio chosen
    Indicates the proportional relationship between two forces, expressing how many times larger or smaller one force is compared to another.
  • B. forceDirection
    Indicates the direction in which a force is applied or exerted in the relationship between entities.
  • C. forceSize
    Indicates a relationship where one entity specifies or constrains the magnitude or size of a force associated with another entity.
  • D. forceType
    Indicates the specific kind or category of force involved in an interaction or event (e.g., physical, legal, military, or other defined force classifications).
  • E. forceBalance
    Indicates that the net forces acting on an entity or system are in equilibrium, resulting in no overall acceleration.
  • 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_69e75a88fdf081908e47ae6e195c14e1 completed April 21, 2026, 11:07 a.m.
NER Named-entity recognition batch_69f46dc1ddd0819089722f45adc50d84 completed May 1, 2026, 9:09 a.m.
PD Predicate disambiguation batch_69f44d8043b081908bbffd7f044b4f26 completed May 1, 2026, 6:51 a.m.
Created at: April 21, 2026, 12:34 p.m.