Triple
T18379581
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | RNO |
E446407
|
entity |
| Predicate | underlyingCompanyMainBrands |
P27763
|
FINISHED |
| Object | Alpine |
—
|
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: Alpine | Statement: [RNO, underlyingCompanyMainBrands, Alpine]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Alpine Context triple: [RNO, underlyingCompanyMainBrands, Alpine]
-
A.
Alpine
Alpine is a small city in the Big Bend region of West Texas, known as a gateway to nearby desert and mountain landscapes and home to Sul Ross State University.
-
B.
Alpine
chosen
Alpine is a French sports car manufacturer renowned for its lightweight performance vehicles and historic success in rally racing.
-
C.
Alpine
Alpine is a small, affluent city at the base of the Wasatch Range in northern Utah, known for its scenic mountain views and residential character.
-
D.
Alp
Alp is a small municipality in the Cerdanya region of the Catalan Pyrenees in northeastern Spain, known for its mountain scenery and proximity to popular ski resorts.
-
E.
Alpen
Alpen is a small municipality in the district of Wesel in North Rhine-Westphalia, Germany, known for its rural character and proximity to the Lower Rhine region.
- 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_69d8b9f370b88190b1e5081c2c238e7f |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e51799e0f4819089e8af04888549bf |
completed | April 19, 2026, 5:57 p.m. |
Created at: April 10, 2026, 10:45 a.m.