Triple
T21097932
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Saint Paul Charlestown Parish |
E519816
|
entity |
| Predicate | isPartOf |
P10
|
FINISHED |
| Object | Nevis |
—
|
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: Nevis | Statement: [Saint Paul Charlestown Parish, isPartOf, Nevis]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nevis Context triple: [Saint Paul Charlestown Parish, isPartOf, Nevis]
-
A.
Nevis
chosen
Nevis is a small volcanic island in the Caribbean known for its lush landscapes, historic plantations, and tranquil beaches.
-
B.
Nevis Range
Nevis Range is a Scottish mountain resort near Fort William, known for its skiing, mountain biking, and access to the slopes of Aonach Mòr.
-
C.
Val Prinsep
Val Prinsep was a 19th-century British painter associated with the Pre-Raphaelite circle, known for his historical and literary-themed works.
-
D.
Mount Keith
Mount Keith is a high Sierra Nevada summit in California, notable as one of the state's prominent fourteen-thousand-foot peaks.
-
E.
Sneeuberge
Sneeuberge is a mountain range in South Africa known for its high peaks, occasional snowfall, and rugged semi-arid landscapes.
- 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_69e0b508d8dc81909be940dafe36c8f7 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e71b5a3a9481908e30fba9717dc461 |
completed | April 21, 2026, 6:38 a.m. |
Created at: April 16, 2026, 2:52 p.m.