Triple
T12063455
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Columbus, Nevada |
E287232
|
entity |
| Predicate | hasCounty |
P285
|
FINISHED |
| Object | Esmeralda County |
E30814
|
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: Esmeralda County | Statement: [Columbus, Nevada, hasCounty, Esmeralda County]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Esmeralda County Context triple: [Columbus, Nevada, hasCounty, Esmeralda County]
-
A.
Esmeralda County
chosen
Esmeralda County is a sparsely populated rural county in western Nevada known for its historic mining towns and vast desert landscapes.
-
B.
Louisa County
Louisa County is a rural county in southeastern Iowa known for its agricultural landscape and small communities along the Iowa and Mississippi rivers.
-
C.
Louisa County
Louisa County is a largely rural county in central Virginia known for its small towns, agricultural landscape, and proximity to Lake Anna.
-
D.
Castro County
Castro County is a rural county in the Texas Panhandle known for its agriculture-based economy and small communities.
-
E.
Marengo County
Marengo County is a rural county in west-central Alabama known for its agricultural economy, historic small towns, and location in the state's Black Belt region.
- 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_69d6ab4846e081908ee7bbd66a6d3459 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d90440dd988190ae2b80367aceb6f7 |
completed | April 10, 2026, 2:08 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f67c5e9fbc819097cf9550378eabee |
completed | May 2, 2026, 10:36 p.m. |
Created at: April 8, 2026, 9:48 p.m.