Triple
T6437397
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dr. Goor Productions |
E129932
|
entity |
| Predicate | founder |
P104
|
FINISHED |
| Object | Dan Goor |
E148092
|
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: Dan Goor | Statement: [Dr. Goor Productions, founder, Dan Goor]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dan Goor Context triple: [Dr. Goor Productions, founder, Dan Goor]
-
A.
Dan Goor
chosen
Dan Goor is an American television writer and producer best known for co-creating the comedy series "Brooklyn Nine-Nine" and his work on shows like "Parks and Recreation."
-
B.
Dan Gilroy
Dan Gilroy is an American screenwriter and director best known for writing and directing the critically acclaimed film "Nightcrawler."
-
C.
David Frankel
David Frankel is an American film and television director best known for helming popular works such as "The Devil Wears Prada" and episodes of "Sex and the City."
-
D.
Matthew Hannam
Matthew Hannam is a Canadian film and television editor known for his work on acclaimed independent films and series.
-
E.
Michael Arndt
Michael Arndt is an Academy Award–winning American screenwriter known for acclaimed films such as Little Miss Sunshine and Toy Story 3.
- 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_69c0084caac48190a7bc2ad8ba44536f |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c06964186c8190aeeb0038f4696032 |
completed | March 22, 2026, 10:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c6538ca31c8190b4a24662c4eeffe9 |
completed | March 27, 2026, 9:53 a.m. |
Created at: March 22, 2026, 4:45 p.m.