Triple
T7346866
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gebbia |
E169401
|
entity |
| Predicate | hasNotableBearer |
P458
|
FINISHED |
| Object | Joe Gebbia |
E30983
|
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: Joe Gebbia | Statement: [Gebbia, hasNotableBearer, Joe Gebbia]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Joe Gebbia Context triple: [Gebbia, hasNotableBearer, Joe Gebbia]
-
A.
Joe Gebbia
chosen
Joe Gebbia is an American designer and entrepreneur best known as a co-founder of the home-sharing platform Airbnb.
-
B.
Jeff Pagliocca
Jeff Pagliocca is a basketball executive best known for serving as the general manager of the WNBA’s Chicago Sky.
-
C.
Owen Vaccaro
Owen Vaccaro is an American child actor best known for his roles in family comedies such as the Daddy's Home films and The House with a Clock in Its Walls.
-
D.
Matt Greenberg
Matt Greenberg is a screenwriter and film producer known for his work on various horror and thriller projects in American cinema.
-
E.
Keith Rabois
Keith Rabois is an American technology executive, entrepreneur, and venture capitalist known for early leadership roles at companies like PayPal, LinkedIn, and Square and for his investments in numerous successful startups.
- 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_69c68a5878888190968ce4d04db8d69f |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f0f0329c8190a0182e3bf62604e5 |
completed | March 27, 2026, 9:04 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7fa916ac881909acee8184b71dc85 |
completed | March 28, 2026, 3:58 p.m. |
Created at: March 27, 2026, 3:05 p.m.