Triple

T1231843
Position Surface form Disambiguated ID Type / Status
Subject John J. Pershing E26459 entity
Predicate educationDegree P6 FINISHED
Object graduate of the United States Military Academy 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: graduate of the United States Military Academy | Statement: [John J. Pershing, educationDegree, graduate of the United States Military Academy]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: educationDegree
Context triple: [John J. Pershing, educationDegree, graduate of the United States Military Academy]
  • A. educationType
    Indicates the specific category or level of education associated with an entity, such as formal, informal, primary, secondary, or higher education.
  • B. academicDegree chosen
    Indicates that an entity holds or has been awarded a specific academic degree.
  • C. educatedAt
    Indicates that an entity received education or formal training at a specified institution or place of learning.
  • D. educationLevelCharacteristic
    Indicates that one entity specifies, describes, or constrains the education level associated with another entity.
  • E. educationLevelAtIssue
    Indicates that the relationship concerns the specific level of education being questioned, disputed, or otherwise central to a particular issue 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_69a4948571c88190a9191e451e6035fd completed March 1, 2026, 7:33 p.m.
NER Named-entity recognition batch_69a4be5a25348190a0665b6324c4d8f5 completed March 1, 2026, 10:31 p.m.
PD Predicate disambiguation batch_69a4bb65d61c8190bf0424ea0019a98b completed March 1, 2026, 10:19 p.m.
Created at: March 1, 2026, 7:47 p.m.