Triple
T22037185
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Michael Kahn (theatre director) |
E544241
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Michael Kahn |
—
|
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 Kahn | Statement: [Michael Kahn (theatre director), name, Michael Kahn]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Michael Kahn Context triple: [Michael Kahn (theatre director), name, Michael Kahn]
-
A.
Michael Kahn
chosen
Michael Kahn is an acclaimed American film editor best known for his long-time collaboration with director Steven Spielberg on numerous major films.
-
B.
Tom Kahn
Tom Kahn was an American social democrat and civil rights activist known for his work with the AFL-CIO and his role in organizing the 1963 March on Washington.
-
C.
Mitch Kertzman
Mitch Kertzman is an American technology executive and entrepreneur best known for his leadership roles in the software and semiconductor industries, including at companies like LSI Logic and Sybase.
-
D.
Phil Rubinstein
Phil Rubinstein is a fictional character portrayed by actor Andrew Robinson, likely appearing in a film or television production.
-
E.
Ian Kahn
Ian Kahn is an American actor best known for playing George Washington on the television series "Turn: Washington's Spies."
- 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_69e11e2f98c8819083e11eab90942a78 |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f127f32edc81909b6898af6621f56f |
completed | April 28, 2026, 9:34 p.m. |
Created at: April 16, 2026, 8:25 p.m.