Triple
T14533978
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tempestt Bledsoe |
E340988
|
entity |
| Predicate | partner |
P1136
|
FINISHED |
| Object | Darryl M. Bell |
E340789
|
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: Darryl M. Bell | Statement: [Tempestt Bledsoe, partner, Darryl M. Bell]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Darryl M. Bell Context triple: [Tempestt Bledsoe, partner, Darryl M. Bell]
-
A.
Darryl M. Bell
chosen
Darryl M. Bell is an American actor best known for his role as Ron Johnson Jr. on the television sitcom "A Different World."
-
B.
Darryl W. Perry
Darryl W. Perry is an American libertarian activist, author, and perennial political candidate known for his involvement in the Libertarian Party and the Free State Project in New Hampshire.
-
C.
Dennis C. Brown
Dennis C. Brown is a television and film composer best known for scoring the long-running animated series "South Park."
-
D.
Darrell K. Williams
Darrell K. Williams is an American higher education leader and retired U.S. Army lieutenant general who serves as president of Hampton University.
-
E.
Ronald J. Williams
Ronald J. Williams is a computer scientist known for his influential contributions to neural networks and machine learning, particularly in the development of backpropagation and reinforcement learning algorithms.
- 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_69d822dac79c8190a84a073f3cbaced5 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69dea053f9bc8190901b9d321811d881 |
completed | April 14, 2026, 8:15 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe0cd6c0dc8190847a887ae51c6c5b |
completed | May 8, 2026, 4:18 p.m. |
Created at: April 10, 2026, 1:22 a.m.