Triple
T8766901
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wonderland (2003 film) |
E208359
|
entity |
| Predicate | cinematographyBy |
P1953
|
FINISHED |
| Object | Michael Grady |
E378827
|
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 Grady | Statement: [Wonderland (2003 film), cinematographyBy, Michael Grady]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Michael Grady Context triple: [Wonderland (2003 film), cinematographyBy, Michael Grady]
-
A.
Michael Grady
chosen
Michael Grady is a cinematographer known for his work on feature films including the biographical legal drama "On the Basis of Sex."
-
B.
Gregory Hess
Gregory Hess was an American protester whose conviction for disorderly conduct during an antiwar demonstration led to the landmark U.S. Supreme Court free speech case Hess v. Indiana.
-
C.
Matthew Aldrich
Matthew Aldrich is an American screenwriter best known for co-writing Pixar’s Academy Award–winning animated film "Coco."
-
D.
Michael Graydon
Michael Graydon is a retired senior Royal Air Force officer who served as a leading commander of British fighter aviation during the late 20th century.
-
E.
Andrew Crawford
Andrew Crawford is a relatively common personal name shared by multiple individuals across various professions, including sports, academia, and the arts.
- 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_69ca835df7e08190ac875664cca8f9ca |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5eeae70c8190adc2bc2846da0fbf |
completed | March 31, 2026, 11:55 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cf51a78a98819083ed4e214cd1fd22 |
completed | April 3, 2026, 5:35 a.m. |
Created at: March 30, 2026, 6:41 p.m.