Triple
T16593234
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Winkler County |
E403141
|
entity |
| Predicate | borderedBy |
P224
|
FINISHED |
| Object | Loving County |
E253851
|
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: Loving County | Statement: [Winkler County, borderedBy, Loving County]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Loving County Context triple: [Winkler County, borderedBy, Loving County]
-
A.
Loving County
chosen
Loving County is a sparsely populated county in western Texas known for being one of the least populous counties in the United States.
-
B.
Plumas County
Plumas County is a rural, mountainous county in northeastern California known for its forests, lakes, and outdoor recreation within the northern Sierra Nevada.
-
C.
Eddy County
Eddy County is a county in southeastern New Mexico known for encompassing Carlsbad Caverns National Park and significant oil and gas production.
-
D.
Carson County
Carson County is a rural county in the Texas Panhandle known for its agricultural economy and small-town communities.
-
E.
Teller County
Teller County is a mountainous county in central Colorado known for its historic gold mining communities, including the city of Cripple Creek.
- 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_69d88387363c8190a97a0c942130de97 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e35d6fcaa48190b1ba7dc3b792041a |
completed | April 18, 2026, 10:31 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a007da8c5048190aaa9350f8fcc8a2e |
completed | May 10, 2026, 12:44 p.m. |
Created at: April 10, 2026, 5:16 a.m.