Triple
T22316233
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brenda Strong |
E551651
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Brenda Strong |
—
|
NE NERFINISHED |
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: Brenda Strong | Statement: [Brenda Strong, name, Brenda Strong]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Brenda Strong Context triple: [Brenda Strong, name, Brenda Strong]
-
A.
Brenda Strong
chosen
Brenda Strong is an American actress best known for her role as Mary Alice Young, the narrator of the television series "Desperate Housewives."
-
B.
Brenda Patterson
Brenda Patterson is an American woman known for being the plaintiff in the landmark U.S. Supreme Court employment discrimination case Patterson v. McLean Credit Union.
-
C.
Brenda Johnson
Brenda Johnson is known as the wife of AC/DC lead singer Brian Johnson.
-
D.
Brenda Walsh
Brenda Walsh is a central teenage character from the 1990s television drama "Beverly Hills, 90210," known for her complex relationships, family dynamics, and coming-of-age storylines.
-
E.
Marlene Warfield
Marlene Warfield is an American actress best known for her powerful supporting roles in film and television during the 1970s and 1980s, including her acclaimed performance in the movie "Network."
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e11e4776588190abb21e5cea79973f |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f157535eb48190adbefbb619cb5fcd |
completed | April 29, 2026, 12:56 a.m. |
Created at: April 16, 2026, 8:42 p.m.