Triple

T11727661
Position Surface form Disambiguated ID Type / Status
Subject TX-27 E278813 entity
Predicate containsCity P294 FINISHED
Object Victoria, Texas E372884 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: Victoria, Texas | Statement: [TX-27, containsCity, Victoria, Texas]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Victoria, Texas
Context triple: [TX-27, containsCity, Victoria, Texas]
  • A. Victoria, Texas chosen
    Victoria, Texas is a small city in southeastern Texas that serves as a regional hub for commerce, healthcare, and legal services along the Gulf Coast.
  • B. Van, Texas
    Van, Texas is a small city in East Texas known historically for its oil production and close-knit rural community.
  • C. Vega, Texas
    Vega, Texas is a small city in the Texas Panhandle that serves as the administrative and commercial hub of Oldham County.
  • D. Venus, Texas
    Venus, Texas is a small town in Johnson and Ellis counties within the Dallas–Fort Worth metropolitan area.
  • E. Alice, Texas
    Alice, Texas is a small city in South Texas that serves as the county seat of Jim Wells County and a regional hub for the surrounding ranching and oil-producing areas.
  • 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_69d6aaffec6881908bead509e8621742 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8a4d70d908190b5f47c2ef501a191 completed April 10, 2026, 7:20 a.m.
NED1 Entity disambiguation (via context triple) batch_69f457f7be0081908f8e1760cc7b8294 completed May 1, 2026, 7:36 a.m.
Created at: April 8, 2026, 9:41 p.m.