Triple

T17701360
Position Surface form Disambiguated ID Type / Status
Subject Refugio, Texas E441306 entity
Predicate hasNearbyCity P350 FINISHED
Object Victoria, Texas NE NERFINISHED

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: [Refugio, Texas, hasNearbyCity, Victoria, Texas]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Victoria, Texas
Context triple: [Refugio, Texas, hasNearbyCity, 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. Justin, Texas
    Justin, Texas is a small city in Denton County within the Dallas–Fort Worth metropolitan area, known for its rural character and proximity to major urban centers.
  • D. Vega, Texas
    Vega, Texas is a small city in the Texas Panhandle that serves as the administrative and commercial hub of Oldham County.
  • E. Venus, Texas
    Venus, Texas is a small town in Johnson and Ellis counties within the Dallas–Fort Worth metropolitan area.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8b9ea20b48190ace88bb46b01e6a9 completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e4715ae1fc81908438a1bba970c6ec completed April 19, 2026, 6:08 a.m.
Created at: April 10, 2026, 10:04 a.m.