Triple
T21068254
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Cat in the Hat (2003 film) |
E519032
|
entity |
| Predicate | editedBy |
P1954
|
FINISHED |
| Object | Don Zimmerman |
—
|
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: Don Zimmerman | Statement: [The Cat in the Hat (2003 film), editedBy, Don Zimmerman]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Don Zimmerman Context triple: [The Cat in the Hat (2003 film), editedBy, Don Zimmerman]
-
A.
Don Zimmerman
chosen
Don Zimmerman is a film editor known for his work on major Hollywood movies, including the family adventure-comedy "Night at the Museum."
-
B.
Gil Zimmerman
Gil Zimmerman is a cinematographer best known for his work on the animated feature film "Monsters vs. Aliens."
-
C.
Dan Zimmerman
Dan Zimmerman is a film editor known for his work on major Hollywood action movies.
-
D.
Dean Zimmerman
Dean Zimmerman is an American philosopher best known for his work in metaphysics, particularly on the nature of time, persistence, and the philosophy of religion.
-
E.
Dean Zimmerman
Dean Zimmerman is an American film editor known for his work on major Hollywood action and science-fiction films.
- 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_69e0b505ef108190b25dd4033e2ff7eb |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e6feb5772481909e32af3b3a69df76 |
completed | April 21, 2026, 4:36 a.m. |
Created at: April 16, 2026, 2:45 p.m.