Triple

T1762738
Position Surface form Disambiguated ID Type / Status
Subject Cowles Lecture E38692 entity
Predicate topicType P26448 FINISHED
Object theoretical econometrics 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: theoretical econometrics | Statement: [Cowles Lecture, topicType, theoretical econometrics]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: topicType
Context triple: [Cowles Lecture, topicType, theoretical econometrics]
  • A. subjectType
    Indicates the classification or category that defines what kind of entity the subject is.
  • B. featuresTopic chosen
    Indicates that something (such as a work, event, or item) prominently includes, focuses on, or is organized around a particular topic.
  • C. primaryTopicOf
    Indicates that a given subject is the main or central topic described by another resource (such as a document, page, or record).
  • D. termType
    Indicates the classification or category of a term within a system, specifying what kind of term it is (e.g., type, role, or function) in relation to others.
  • E. category
    Indicates that one entity is classified as a member or type within the grouping or class defined by another entity.
  • 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_69a8862d562481908d7025a1c1f67c0d completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69ab173936b4819097332ee185996bbd completed March 6, 2026, 6:04 p.m.
PD Predicate disambiguation batch_69aa61c9e06c819085489e00cfe72153 completed March 6, 2026, 5:10 a.m.
Created at: March 4, 2026, 7:31 p.m.