Triple
T3286938
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1492 Pictures |
E69003
|
entity |
| Predicate | hasProducer |
P30366
|
FINISHED |
| Object | Michael Barnathan |
E156798
|
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: Michael Barnathan | Statement: [1492 Pictures, hasProducer, Michael Barnathan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Michael Barnathan Context triple: [1492 Pictures, hasProducer, Michael Barnathan]
-
A.
Michael Barnathan
chosen
Michael Barnathan is an American film producer known for working on major studio hits such as the "Night at the Museum" series and the "Harry Potter" films.
-
B.
Nick Barton
Nick Barton is a prominent evolutionary biologist known for his influential work on the genetics of adaptation and speciation.
-
C.
Ian Bryce
Ian Bryce is a British film producer known for his work on major Hollywood blockbusters such as Saving Private Ryan and the Transformers series.
-
D.
Christopher Benstead
Christopher Benstead is a British composer and music editor known for his film scores and sound work on major movies, including collaborations with director Guy Ritchie.
-
E.
Sean Barton
Sean Barton is a film editor known for his work on various feature films, including the drama "Tea with Mussolini."
- 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_69ad859d45748190b0742408c954b39f |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb05779d08190a5517951e71b1380 |
completed | March 8, 2026, 5:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b360980b088190a9edd7f1b1773926 |
completed | March 13, 2026, 12:55 a.m. |
Created at: March 8, 2026, 3:10 p.m.