Triple
T23383526
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jelly Industries, Inc. |
E593813
|
entity |
| Predicate | hasKeyPerson |
P256
|
FINISHED |
| Object | Biz Stone |
—
|
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: Biz Stone | Statement: [Jelly Industries, Inc., hasKeyPerson, Biz Stone]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Biz Stone Context triple: [Jelly Industries, Inc., hasKeyPerson, Biz Stone]
-
A.
Biz Stone
chosen
Biz Stone is an American entrepreneur and software developer best known as one of the co-founders of Twitter and a prominent figure in the social media industry.
-
B.
Dustin Moskovitz
Dustin Moskovitz is an American entrepreneur and philanthropist best known as a co-founder of Facebook and the productivity software company Asana.
-
C.
Brian Armstrong
Brian Armstrong is an American entrepreneur best known as the co-founder and CEO of the cryptocurrency exchange Coinbase.
-
D.
Steve Levine
Steve Levine is a British record producer best known for his work in the 1980s with artists such as Culture Club and The Beach Boys.
-
E.
Scott Belsky
Scott Belsky is an American entrepreneur, author, and investor best known as the co-founder of the creative platform Behance and as a longtime product leader at Adobe.
- 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_69e25d268a50819095f2fd479da8ef3f |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f1a496ae34819090e86c89eef6d2dc |
completed | April 29, 2026, 6:26 a.m. |
Created at: April 17, 2026, 5:34 p.m.