Triple
T12109689
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wilder |
E288390
|
entity |
| Predicate | hasNotableBearer |
P458
|
FINISHED |
| Object |
Craig Wilder
Craig Wilder is an American historian known for his scholarship on race, slavery, and the history of higher education in the United States.
|
E965677
|
NE FINISHED |
How this triple was built (4 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: Craig Wilder | Statement: [Wilder, hasNotableBearer, Craig Wilder]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Craig Wilder Context triple: [Wilder, hasNotableBearer, Craig Wilder]
-
A.
Eric Waller
Eric Waller is an entrepreneur best known as a co-founder of the mobile-focused ticketing platform SeatGeek.
-
B.
Craig Weller
Craig Weller is an American entrepreneur best known as one of the co-founders of the natural and organic grocery chain Whole Foods Market.
-
C.
Craig Weller
Craig Weller is a business figure known for co-founding an enterprise alongside Renee Lawson Hardy.
-
D.
Blake Worsley
Blake Worsley is a Canadian former competitive swimmer who specialized in freestyle events and represented Canada at international competitions, including the Olympic Games.
-
E.
Jonathan Ward
Jonathan Ward is an American actor best known for his work in 1980s film and television, including leading roles in family and science fiction movies.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Craig Wilder Triple: [Wilder, hasNotableBearer, Craig Wilder]
Generated description
Craig Wilder is an American historian known for his scholarship on race, slavery, and the history of higher education in the United States.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Craig Wilder Target entity description: Craig Wilder is an American historian known for his scholarship on race, slavery, and the history of higher education in the United States.
-
A.
Eric Waller
Eric Waller is an entrepreneur best known as a co-founder of the mobile-focused ticketing platform SeatGeek.
-
B.
Craig Weller
Craig Weller is an American entrepreneur best known as one of the co-founders of the natural and organic grocery chain Whole Foods Market.
-
C.
Craig Weller
Craig Weller is a business figure known for co-founding an enterprise alongside Renee Lawson Hardy.
-
D.
Blake Worsley
Blake Worsley is a Canadian former competitive swimmer who specialized in freestyle events and represented Canada at international competitions, including the Olympic Games.
-
E.
Jonathan Ward
Jonathan Ward is an American actor best known for his work in 1980s film and television, including leading roles in family and science fiction movies.
- F. None of above. chosen
Provenance (5 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_69d6ab4a5c448190a110d1273314b21a |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d9156709288190b4684cb19037dc38 |
completed | April 10, 2026, 3:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f5f67b3f2c8190bcb2120781f91220 |
completed | May 2, 2026, 1:04 p.m. |
| NEDg | Description generation | batch_69f5fdea1afc8190b39557fdc571e300 |
completed | May 2, 2026, 1:36 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f5feeaf2e48190995f282b02a9caaf |
completed | May 2, 2026, 1:40 p.m. |
Created at: April 8, 2026, 9:49 p.m.