Triple

T35426734
Position Surface form Disambiguated ID Type / Status
Subject Milner-Barry Gambit in the French Defence E1023939 entity
Predicate learningFocus P6235 FINISHED
Object understanding compensation for material 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: understanding compensation for material | Statement: [Milner-Barry Gambit in the French Defence, learningFocus, understanding compensation for material]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: learningFocus
Context triple: [Milner-Barry Gambit in the French Defence, learningFocus, understanding compensation for material]
  • A. educationalFocus chosen
    Indicates the primary subject area or theme that an educational activity, program, or resource is centered on.
  • B. learn
    Indicates that an entity acquires knowledge, skills, or understanding from another entity, source, or experience.
  • C. educationGoal
    Indicates a relationship where an entity has a specific educational aim, objective, or intended learning outcome it is working toward.
  • D. studentEngagementFocus
    Indicates that the primary emphasis of an activity, strategy, or context is on promoting, sustaining, or enhancing students’ active engagement.
  • E. focusMode
    Indicates that an entity is currently in a concentrated or distraction-minimized state directed toward a specific task, target, or context.
  • 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_69f76df6704081909900c60be10d5849 completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69f79da9f80c8190b0afd8509f28747b completed May 3, 2026, 7:10 p.m.
PD Predicate disambiguation batch_69f79617d40481909ba372f94209c08b completed May 3, 2026, 6:38 p.m.
Created at: May 3, 2026, 4:03 p.m.