Triple
T1088880
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lander County |
E24114
|
entity |
| Predicate | borders |
P224
|
FINISHED |
| Object | Nye County |
E29687
|
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: Nye County | Statement: [Lander County, borders, Nye County]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nye County Context triple: [Lander County, borders, Nye County]
-
A.
Nye County
chosen
Nye County is a large, sparsely populated county in south-central Nevada known for its desert landscapes, mining history, and proximity to the Nevada Test Site.
-
B.
Churchill County
Churchill County is a largely rural county in Nevada known for its agricultural communities, desert landscapes, and the city of Fallon as its county seat.
-
C.
Lander County
Lander County is a sparsely populated, rural county in north-central Nevada known for its mining history and wide expanses of high desert and mountain terrain.
-
D.
Mineral County
Mineral County is a rural county in western Nevada known for its mining history, desert landscapes, and the Hawthorne Army Depot.
-
E.
Elko County
Elko County is a large, sparsely populated county in northeastern Nevada known for its mining, ranching, and wide-open high desert landscapes.
- 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_69a49404428c819092dcc9632f5f7b8b |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4b97d85708190a1630256648aa4a2 |
completed | March 1, 2026, 10:11 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad1c8ee9dc8190b9f6a46841003e8a |
completed | March 8, 2026, 6:51 a.m. |
Created at: March 1, 2026, 7:42 p.m.