Triple

T3915758
Position Surface form Disambiguated ID Type / Status
Subject CS E88834 entity
Predicate standsFor P590 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: [CS, standsFor, College Station]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: College Station
Context triple: [CS, standsFor, 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. North Lake College Station
    North Lake College Station is a Dallas Area Rapid Transit (DART) light rail stop serving the North Lake College area in Irving, Texas.
  • C. Prairie View, Texas
    Prairie View, Texas is a small city in Waller County best known as the home of Prairie View A&M University and as part of the greater Houston metropolitan region.
  • D. Tarleton
    Tarleton is a village in Lancashire, England, situated in a rural area of the West Lancashire Coastal Plain near the River Douglas.
  • E. West University Place, Texas
    West University Place, Texas is a small, affluent residential city in the Houston metropolitan area known for its high property values, strong public services, and proximity to Rice University.
  • 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_69aed955229881909e85e73ffab1d343 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aeed3a0d4c8190bb952d920b054a7f completed March 9, 2026, 3:54 p.m.
NED1 Entity disambiguation (via context triple) batch_69b528606ef88190a06ab8073d1df945 completed March 14, 2026, 9:20 a.m.
Created at: March 9, 2026, 3:22 p.m.