Triple
T14414104
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Little Children |
E357403
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object | Ron Yerxa |
E690778
|
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: Ron Yerxa | Statement: [Little Children, producer, Ron Yerxa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ron Yerxa Context triple: [Little Children, producer, Ron Yerxa]
-
A.
Ron Yerxa
chosen
Ron Yerxa is an American film producer known for his work on acclaimed independent and studio films such as "Little Miss Sunshine," "Election," and "Cold Mountain."
-
B.
Kevin Yagher
Kevin Yagher is an American special effects and makeup artist and director best known for his work on horror and fantasy films and for creating iconic genre characters.
-
C.
Eric Danchick
Eric Danchick is a film producer known for his work on the movie "Bound 2."
-
D.
Chris Chesser
Chris Chesser is an American film and television producer best known for producing the hit baseball comedy film "Major League."
-
E.
Daniel Yost
Daniel Yost is an American screenwriter best known for co-writing the acclaimed 1989 film "Drugstore Cowboy."
- 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_69d82793421c8190861eb0e673b085de |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de90cb3c708190822f5506ebf7ee9d |
completed | April 14, 2026, 7:08 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fff288ba908190a36c4784331d1e60 |
completed | May 10, 2026, 2:50 a.m. |
Created at: April 10, 2026, 1:17 a.m.