Triple
T21812411
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Berry Berenson |
E538510
|
entity |
| Predicate | hasFamilyName |
P18
|
FINISHED |
| Object | Berenson |
—
|
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: Berenson | Statement: [Berry Berenson, hasFamilyName, Berenson]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Berenson Context triple: [Berry Berenson, hasFamilyName, Berenson]
-
A.
John Benenson
John Benenson is a notable individual who shares the Benenson surname, recognized as a distinguished bearer of that family name.
-
B.
Berry Berenson
chosen
Berry Berenson was an American photographer, actress, and model known for her work in film and fashion and for her marriage to actor Anthony Perkins.
-
C.
Red Berenson
Red Berenson is a legendary ice hockey coach and former NHL player best known for transforming the University of Michigan Wolverines into a perennial collegiate powerhouse.
-
D.
Charles Benenson
Charles Benenson was an American real estate investor and philanthropist known for building a major property empire and supporting numerous cultural and charitable causes.
-
E.
Benson
Benson is a gumball machine-headed park manager and recurring authority figure in the animated television series "Regular Show."
- 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_69e0c473f0f8819086c9d1b4a143bd67 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69f07cc7ec1c8190a5420b44a49ae32f |
completed | April 28, 2026, 9:24 a.m. |
Created at: April 16, 2026, 6:53 p.m.