Triple

T1119971
Position Surface form Disambiguated ID Type / Status
Subject College of Science E11186 entity
Predicate city P40 FINISHED
Object College Station E15336 NE 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: College Station | Statement: [College of Science, city, College Station]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: College Station
Context triple: [College of Science, city, College Station]
  • A. College Station, Texas chosen
    College Station, Texas is a central Texas city best known as the home of Texas A&M University and its large student-centered community.
  • B. Tarleton
    Tarleton is a village in Lancashire, England, situated in a rural area of the West Lancashire Coastal Plain near the River Douglas.
  • C. University Park, Texas
    University Park, Texas is an affluent suburban city in the Dallas–Fort Worth area best known as the home of Southern Methodist University.
  • D. San Marcos
    San Marcos is a city that maintains an official twinning partnership with Biel/Bienne in Switzerland, reflecting cultural and municipal cooperation between the two communities.
  • E. San Marcos
    San Marcos is a city in western Guatemala that serves as the capital of the San Marcos Department near the country’s highest peak, Volcán Tajumulco.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

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_69a493252a648190ac48f8742474a5e8 completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a4bbbca3348190a607ce147b2ae70e completed March 1, 2026, 10:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac7f2dc92481909ee6d9d6d4257f1b completed March 7, 2026, 7:40 p.m.
Created at: March 1, 2026, 7:43 p.m.