Triple
T7201725
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stanley Unwin |
E168761
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Unwin |
E246842
|
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: Unwin | Statement: [Stanley Unwin, familyName, Unwin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Unwin Context triple: [Stanley Unwin, familyName, Unwin]
-
A.
Unwin
chosen
Unwin is the surname of Gary "Eggsy" Unwin, the working-class protagonist of the Kingsman film series.
-
B.
Ewins
Ewins is a surname variant of Ewing, typically of Scottish or Irish origin.
-
C.
Hailwood
Hailwood is the surname of legendary British motorcycle racer Mike Hailwood, widely regarded as one of the greatest riders in the history of the sport.
-
D.
The Whitworth
The Whitworth is a prominent art gallery and museum in Manchester, England, renowned for its collections of fine art, textiles, and wallpapers and its integration with the surrounding park.
-
E.
Haynes
Haynes is a surname most notably associated with American filmmaker Todd Haynes, known for his influential work in independent cinema.
- 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_69c68a5376748190bb500f03df86e93e |
completed | March 27, 2026, 1:46 p.m. |
| NER | Named-entity recognition | batch_69c6e94971508190bb38184c9af2fe51 |
completed | March 27, 2026, 8:32 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7bfb0f4688190a677b818a0b3619c |
completed | March 28, 2026, 11:46 a.m. |
Created at: March 27, 2026, 2:52 p.m.