Triple
T15395090
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bradley Wiggins |
E368157
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Wiggins |
E247928
|
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: Wiggins | Statement: [Bradley Wiggins, familyName, Wiggins]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wiggins Context triple: [Bradley Wiggins, familyName, Wiggins]
-
A.
Wiggins
chosen
Wiggins is a surname most prominently associated with American former WNBA basketball player Candice Wiggins.
-
B.
Wiggins
Wiggins is a small city in Stone County, Mississippi, known for its pine forests and role as a local commercial center in the southern part of the state.
-
C.
Winkleman
Winkleman is a surname most notably associated with British actress Sophie Winkleman and her extended family, which includes media and entertainment figures.
-
D.
Weeley
Weeley is a small village and civil parish in the Tendring district of Essex, England, known for its rural character and proximity to the Essex coast.
-
E.
Wilder Williams
Wilder Williams is an individual notable enough to be recognized as a prominent bearer of the given name Wilder.
- 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_69d85a16c68c819099c1b547fbc87b32 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03e8ac79081908ac79c0b3e7587ff |
completed | April 16, 2026, 1:42 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff13523f548190beafd130f8741465 |
completed | May 9, 2026, 10:58 a.m. |
Created at: April 10, 2026, 3:19 a.m.