Triple
T19636746
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Don Gullett |
E471417
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Gullett
Gullett is a surname most notably associated with former Major League Baseball pitcher Don Gullett.
|
E1388601
|
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: Gullett | Statement: [Don Gullett, familyName, Gullett]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gullett Context triple: [Don Gullett, familyName, Gullett]
-
A.
Bivins
Bivins is a surname most notably associated with Michael Bivins, an American singer, rapper, and music executive known for his work with New Edition and Bell Biv DeVoe.
-
B.
Spottiswoode
Spottiswoode is a surname most notably associated with British-Canadian film director Roger Spottiswoode.
-
C.
O'Steen
O'Steen is a surname most notably associated with American film editor Sam O'Steen, known for his work on several acclaimed Hollywood films.
-
D.
Bubley
Bubley is the surname of Esther Bubley, an influential American photographer known for her documentary work in the mid-20th century.
-
E.
Trulaske
Trulaske is the commonly used name for the Robert J. Trulaske, Sr. College of Business at the University of Missouri, a business school offering undergraduate and graduate programs in fields such as accounting, finance, and management.
- 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: Gullett Triple: [Don Gullett, familyName, Gullett]
Generated description
Gullett is a surname most notably associated with former Major League Baseball pitcher Don Gullett.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Gullett Target entity description: Gullett is a surname most notably associated with former Major League Baseball pitcher Don Gullett.
-
A.
Bivins
Bivins is a surname most notably associated with Michael Bivins, an American singer, rapper, and music executive known for his work with New Edition and Bell Biv DeVoe.
-
B.
Spottiswoode
Spottiswoode is a surname most notably associated with British-Canadian film director Roger Spottiswoode.
-
C.
O'Steen
O'Steen is a surname most notably associated with American film editor Sam O'Steen, known for his work on several acclaimed Hollywood films.
-
D.
Bubley
Bubley is the surname of Esther Bubley, an influential American photographer known for her documentary work in the mid-20th century.
-
E.
Trulaske
Trulaske is the commonly used name for the Robert J. Trulaske, Sr. College of Business at the University of Missouri, a business school offering undergraduate and graduate programs in fields such as accounting, finance, and management.
- 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_69d8e511f28481909f4bc3ea9191e54a |
completed | April 10, 2026, 11:54 a.m. |
| NER | Named-entity recognition | batch_69e641070528819085663c439f50148e |
completed | April 20, 2026, 3:06 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a077ee2ba00819082c50c6b163becf4 |
completed | May 15, 2026, 8:15 p.m. |
| NEDg | Description generation | batch_6a077fb5d7288190a691e312ec22789b |
completed | May 15, 2026, 8:19 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a07810b1de88190a2516712767fde52 |
completed | May 15, 2026, 8:24 p.m. |
Created at: April 10, 2026, 1:44 p.m.