Triple
T14969450
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hockley County |
E373277
|
entity |
| Predicate | hasBorderWith |
P224
|
FINISHED |
| Object | Yoakum County |
E396805
|
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: Yoakum County | Statement: [Hockley County, hasBorderWith, Yoakum County]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Yoakum County Context triple: [Hockley County, hasBorderWith, Yoakum County]
-
A.
Yoakum County
chosen
Yoakum County is a rural county in western Texas known for its agriculture and oil production.
-
B.
Mayes County
Mayes County is a county in northeastern Oklahoma known for its mix of small towns, agricultural areas, and recreational lakes.
-
C.
Fisher County
Fisher County is a rural county in west-central Texas known for its agricultural economy and small, sparsely populated communities.
-
D.
Van Zandt County
Van Zandt County is a rural county in northeastern Texas known for its agricultural heritage and small-town communities.
-
E.
Cottle County
Cottle County is a sparsely populated rural county in north-central Texas known for its ranching, agriculture, and small-town communities.
- 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_69d85ccbbcd48190acb56e7cf104d8ad |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded6e44cb0819096e09f8026ef8174 |
completed | April 15, 2026, 12:08 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff0b3216fc8190b79740a993b98cb3 |
completed | May 9, 2026, 10:23 a.m. |
Created at: April 10, 2026, 2:49 a.m.