Triple
T19453394
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Titan |
E486672
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object | Fred Berger |
—
|
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: Fred Berger | Statement: [The Titan, producer, Fred Berger]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Fred Berger Context triple: [The Titan, producer, Fred Berger]
-
A.
Fred Berger
chosen
Fred Berger is a film producer best known for his work on acclaimed movies such as "La La Land" and other high-profile Hollywood projects.
-
B.
Edward Berger
Edward Berger is a German film and television director known for his acclaimed work on series like "Patrick Melrose" and the Oscar-winning war drama "All Quiet on the Western Front."
-
C.
Glenn Berger
Glenn Berger is an American screenwriter best known for co-writing major animated films such as the Kung Fu Panda series.
-
D.
Robert G. Bergman
Robert G. Bergman is an American organic chemist renowned for his pioneering work in organometallic chemistry and C–H bond activation.
-
E.
Eddie Felson
Eddie Felson is a fiercely ambitious, self-destructive pool hustler whose rise and fall in the world of high-stakes billiards explores themes of pride, integrity, and redemption.
- 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_69d8e8d86d608190bd199a98d0297f27 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e6339407a08190a3e0213bfbb4df3d |
completed | April 20, 2026, 2:09 p.m. |
Created at: April 10, 2026, 1:38 p.m.