Triple
T13439834
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wright |
E320328
|
entity |
| Predicate | hasNotableBearer |
P458
|
FINISHED |
| Object | Dorian Yates Wright |
E439268
|
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: Dorian Yates Wright | Statement: [Wright, hasNotableBearer, Dorian Yates Wright]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dorian Yates Wright Context triple: [Wright, hasNotableBearer, Dorian Yates Wright]
-
A.
Dorian Yates
chosen
Dorian Yates is a legendary English professional bodybuilder renowned for his massively muscular, grainy physique and six consecutive Mr. Olympia titles in the 1990s.
-
B.
Ronnie Coleman
Ronnie Coleman is an American professional bodybuilder widely regarded as one of the greatest in the sport’s history, best known for winning eight Mr. Olympia titles.
-
C.
Frank Zane
Frank Zane is an American bodybuilder renowned for his aesthetic, proportioned physique and three-time Mr. Olympia titles in the late 1970s.
-
D.
Rory St. Clair Gainer
Rory St. Clair Gainer is a British businessman best known as the husband of Swedish actress Rebecca Ferguson.
-
E.
Ken Duken
Ken Duken is a German actor and director known for his work in both domestic and international film and television productions.
- 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_69d80761e6cc8190a90c844589998ecc |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbaee5ec488190bd0c1e990dbd2bc2 |
completed | April 12, 2026, 2:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7399421908190a7750e37c89a73f6 |
completed | May 3, 2026, 12:03 p.m. |
Created at: April 9, 2026, 9:40 p.m.