Triple
T11080704
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ward County |
E261982
|
entity |
| Predicate | bordersOn |
P224
|
FINISHED |
| Object | Reeves County |
E386537
|
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: Reeves County | Statement: [Ward County, bordersOn, Reeves County]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Reeves County Context triple: [Ward County, bordersOn, Reeves County]
-
A.
Reeves County
chosen
Reeves County is a sparsely populated county in western Texas known for its oil and gas production and desert landscapes.
-
B.
Brewster County
Brewster County is a vast, sparsely populated county in West Texas known for encompassing much of the Big Bend region along the Rio Grande.
-
C.
Gillespie County
Gillespie County is a central Texas county known for its scenic Hill Country landscapes, German heritage, and the historic town of Fredericksburg.
-
D.
Nolan County
Nolan County is a county in west-central Texas known for its wind energy production and county seat, Sweetwater.
-
E.
McLennan County
McLennan County is a county in central Texas best known for encompassing the city of Waco, home to Baylor 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_69d6aa9983c08190b0ef61603b69feac |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d79996d9408190b159d14b23c25ed1 |
completed | April 9, 2026, 12:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a002d92c9788190aa4523a1e47bc561 |
completed | May 10, 2026, 7:02 a.m. |
Created at: April 8, 2026, 9:27 p.m.