Triple
T16593235
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Winkler County |
E403141
|
entity |
| Predicate | hasSettlement |
P1068
|
FINISHED |
| Object | Kermit, 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: Kermit, Texas | Statement: [Winkler County, hasSettlement, Kermit, Texas]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kermit, Texas Context triple: [Winkler County, hasSettlement, Kermit, Texas]
-
A.
Kermit, Texas
chosen
Kermit, Texas is a small West Texas city known for its oil industry roots and role as the principal community in Winkler County.
-
B.
Kurten, Texas
Kurten, Texas is a small rural town in east-central Texas that is part of the Bryan–College Station metropolitan area.
-
C.
Kirbyville, Texas
Kirbyville, Texas is a small city in Southeast Texas known for its rural character and location within the heavily forested Piney Woods region.
-
D.
Kyle, Texas
Kyle, Texas is a rapidly growing small city in Central Texas located between Austin and San Marcos, known for its suburban character and proximity to major highways.
-
E.
Keene, Texas
Keene, Texas is a small city in North Texas known for its close-knit community and association with Southwestern Adventist University.
- 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_69d88387363c8190a97a0c942130de97 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e35d6fcaa48190b1ba7dc3b792041a |
completed | April 18, 2026, 10:31 a.m. |
Created at: April 10, 2026, 5:16 a.m.