Triple
T22226374
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Greg Wise |
E549347
|
entity |
| Predicate | memberOf |
P10
|
FINISHED |
| Object | Wise family |
—
|
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: Wise family | Statement: [Greg Wise, memberOf, Wise family]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wise family Context triple: [Greg Wise, memberOf, Wise family]
-
A.
Wise family
chosen
The Wise family is a British showbusiness family that includes actor and comedian Greg Wise and his relatives, some of whom are connected to the entertainment industry.
-
B.
Bright family
The Bright family is a prominent benefactor family associated with Harvard University, recognized for their significant philanthropic contributions that led to the naming of the Bright-Landry Hockey Center.
-
C.
Sweet family
The Sweet family is a notable family group recognized primarily in connection with Joe Mack.
-
D.
Sen family
The Sen family is the hereditary lineage of Japanese tea masters descended from Sen no Rikyū, central to the development and transmission of the Japanese tea ceremony.
-
E.
Sen family
The Sen family is a prominent Indian film dynasty known for its multi-generational contributions to Bengali and Hindi cinema.
- 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_69e11e403d6481909a94d0aaf157f6ef |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f12bee8de8819091ec5d14ea057f9e |
completed | April 28, 2026, 9:51 p.m. |
Created at: April 16, 2026, 8:37 p.m.