Triple
T22133033
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Northern West Virginia |
E546951
|
entity |
| Predicate | includesCity |
P3207
|
FINISHED |
| Object | Fairmont |
—
|
NE NERFINISHED |
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: Fairmont | Statement: [Northern West Virginia, includesCity, Fairmont]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Fairmont Context triple: [Northern West Virginia, includesCity, Fairmont]
-
A.
Fairmont
Fairmont is a global luxury hotel brand known for its historic landmark properties and upscale accommodations.
-
B.
Fairmont
Fairmont is a small unincorporated community and census-designated place located in Will County, Illinois, United States.
-
C.
Fairmont
chosen
Fairmont is a city in north-central West Virginia known historically for its role in the coal industry and as part of the greater Morgantown metropolitan area.
-
D.
Fairmont Station
Fairmont Station is a light rail stop on Metro Transit's S Line in the Minneapolis–Saint Paul metropolitan area.
-
E.
Fairmont Hairpin
Fairmont Hairpin is a famously tight, slow-speed corner on the Monaco Grand Prix street circuit, known as one of the most iconic and challenging hairpins in Formula 1 racing.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e11e39bf348190b541bfa16a7b71e0 |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f129b81d5c819085fd18bf3ae28333 |
completed | April 28, 2026, 9:42 p.m. |
Created at: April 16, 2026, 8:32 p.m.