Triple

T1005408
Position Surface form Disambiguated ID Type / Status
Subject Model Diplomacy E21697 entity
Predicate learningOutcome P12786 FINISHED
Object policy analysis skills 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: policy analysis skills | Statement: [Model Diplomacy, learningOutcome, policy analysis skills]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: learningOutcome
Context triple: [Model Diplomacy, learningOutcome, policy analysis skills]
  • A. programOutcome
    Indicates the resulting state, effect, or consequence produced by executing or completing a program.
  • B. educationalObjective chosen
    Indicates the intended learning goal, skill, or competency that an educational resource, activity, or program is designed to achieve.
  • C. missionOutcome
    Indicates the result or consequence of a mission, specifying whether and how the mission’s objectives were achieved or failed.
  • D. educationalActivity
    Indicates an action or relationship in which one entity engages in or provides a learning or teaching activity for another.
  • E. course
    Indicates that an entity is an academic class or unit of instruction offered within an educational program.
  • 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_69a493c53e648190ae8cb76c433fd9a7 completed March 1, 2026, 7:30 p.m.
NER Named-entity recognition batch_69a4b51303548190a5ee3c0797fc3245 completed March 1, 2026, 9:52 p.m.
PD Predicate disambiguation batch_69a4b2b2e7108190b338b6c19d4aff55 completed March 1, 2026, 9:42 p.m.
Created at: March 1, 2026, 7:41 p.m.