Triple
T14637751
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 99 Homes |
E343649
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object | Kevin Turen |
E926437
|
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: Kevin Turen | Statement: [99 Homes, producer, Kevin Turen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kevin Turen Context triple: [99 Homes, producer, Kevin Turen]
-
A.
Kevin Turen
chosen
Kevin Turen is an American film and television producer known for working on acclaimed independent projects and prestige series.
-
B.
Kevin Crowe
Kevin Crowe is a songwriter best known for co-writing the hit track "Young, Wild & Free."
-
C.
Thomas Leitch
Thomas Leitch is a scholar of film and literary adaptation studies, known for his influential work on how literature is transformed into cinema.
-
D.
Roger Ebert
Roger Ebert was a pioneering American film critic, journalist, and screenwriter renowned for his influential reviews, television programs, and role in popularizing accessible, mainstream film criticism.
-
E.
Gene Siskel
Gene Siskel was a prominent American film critic best known for his influential movie review television programs and long-running partnership with fellow critic Roger Ebert.
- 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_69d822dffc3c8190aa173b90761bffda |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb4aca6448190adf1042dfbfef716 |
completed | April 14, 2026, 9:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fde16e85488190b0dcc2ccd2f5df4d |
completed | May 8, 2026, 1:13 p.m. |
Created at: April 10, 2026, 1:26 a.m.