Triple
T21634207
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | I Kill Giants |
E533911
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object | Michael Barnathan |
—
|
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: Michael Barnathan | Statement: [I Kill Giants, producer, Michael Barnathan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Michael Barnathan Context triple: [I Kill Giants, producer, 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.
Michael Bannister
Michael Bannister is a musician best known as a member of the Scottish indie rock supergroup Reindeer Section.
-
C.
Leo Barnes
Leo Barnes is a former police sergeant turned security chief who becomes a key resistance figure fighting to end the annual Purge in the dystopian horror-thriller film series.
-
D.
Nick Barton
Nick Barton is a British film producer best known for his work on the hit comedy-drama film "Calendar Girls."
-
E.
Nick Barton
Nick Barton is a prominent evolutionary biologist known for his influential work on the genetics of adaptation and speciation.
- 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_69e0c465ae7481908577b7209fdb2a77 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ef52192e388190a3f316e33f452561 |
completed | April 27, 2026, 12:10 p.m. |
Created at: April 16, 2026, 6:35 p.m.