Triple
T5828274
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Scafell |
E129281
|
entity |
| Predicate | listedAs |
P310
|
FINISHED |
| Object | Wainwright |
E518451
|
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: Wainwright | Statement: [Scafell, listedAs, Wainwright]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wainwright Context triple: [Scafell, listedAs, Wainwright]
-
A.
Wainwright
chosen
Wainwright is a renowned series of guidebooks and classifications of the fells of the English Lake District, created by British fellwalker and author Alfred Wainwright.
-
B.
Wainwright
Wainwright is a small Inupiat community and coastal village in northern Alaska, located along the Arctic Ocean.
-
C.
Wainwright
Wainwright is a surname most prominently associated with the Canadian-American singer-songwriter Rufus Wainwright and his musical family.
-
D.
Wray
Wray is the surname of Fay Wray, the Canadian-American actress best known for her iconic role in the classic 1933 film "King Kong."
-
E.
Wetherden
Wetherden is a small rural village and civil parish in the English county of Suffolk.
- 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_69c00849d55481908b4f9f5543e0bf6d |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c03467dfe48190b51757b33681bc20 |
completed | March 22, 2026, 6:26 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c09863be3c8190bba357bf64e22917 |
completed | March 23, 2026, 1:33 a.m. |
Created at: March 22, 2026, 3:53 p.m.