Triple
T9824658
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Saving Mr. Banks |
E238623
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object | Philip Steuer |
E238623
|
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: Philip Steuer | Statement: [Saving Mr. Banks, producer, Philip Steuer]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Philip Steuer Context triple: [Saving Mr. Banks, producer, Philip Steuer]
-
A.
Philip Steuer
chosen
Philip Steuer is a film producer best known for his work on major studio projects, including the Disney drama "Saving Mr. Banks."
-
B.
Michael Hecht
Michael Hecht is the birth name of Michael Howard, a British Conservative politician who served as Leader of the Opposition and Home Secretary.
-
C.
Michael Hecht
Michael Hecht is a scientist best known for leading NASA’s MOXIE experiment on the Perseverance rover, which demonstrates in-situ oxygen production on Mars.
-
D.
Michael Bergmann
Michael Bergmann is an American analytic philosopher known for his work in epistemology, particularly on skepticism, justification, and religious epistemology.
-
E.
Stephen Endlicher
Stephen Endlicher was a 19th-century Austrian botanist and linguist known for his influential work in plant taxonomy and classification.
- 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_69ca84e0dd1881909800765d1e21f735 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdb3181c688190afea3b27ee392a30 |
completed | April 2, 2026, 12:06 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d354c521dc819084b09c9a57c1a26c |
completed | April 6, 2026, 6:37 a.m. |
Created at: March 30, 2026, 8:31 p.m.