Triple
T11235297
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Frantic |
E265926
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object | Thom Mount |
E65498
|
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: Thom Mount | Statement: [Frantic, producer, Thom Mount]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Thom Mount Context triple: [Frantic, producer, Thom Mount]
-
A.
Thom Mount
chosen
Thom Mount is an American film producer and former president of Universal Pictures known for overseeing and producing a range of influential Hollywood films.
-
B.
Tim Thomerson
Tim Thomerson is an American actor and comedian best known for his roles in cult science fiction and action films such as the "Trancers" series.
-
C.
Chris Thomson
Chris Thomson is a film and television director known for his work adapting stories for the screen, including directing the adaptation of "Trucks."
-
D.
Chris Thomas
Chris Thomas is a renowned British record producer known for his work with major rock acts such as The Beatles, Pink Floyd, and the Sex Pistols.
-
E.
Nick Townsend
Nick Townsend is a central male character in the 1932 film "Blonde Venus," involved in the dramatic romantic and moral conflicts that drive the story.
- 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_69d6aac656d48190b275efaa7d6074ee |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e903b8ec81909f9c89776d35c650 |
completed | April 9, 2026, 5:59 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e4ad56013481909f931505824e3b42 |
completed | April 19, 2026, 10:24 a.m. |
Created at: April 8, 2026, 9:30 p.m.