Triple
T9578882
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Scrubs |
E231117
|
entity |
| Predicate | productionCompany |
P490
|
FINISHED |
| Object | Doozer |
E494434
|
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: Doozer | Statement: [Scrubs, productionCompany, Doozer]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Doozer Context triple: [Scrubs, productionCompany, Doozer]
-
A.
Doozer
chosen
Doozer is a television production company founded by Bill Lawrence, best known for producing series such as Scrubs, Cougar Town, and Ted Lasso.
-
B.
Deezle
Deezle is an American hip-hop and R&B record producer best known for his work with Lil Wayne, including contributions to the hit album "Tha Carter III."
-
C.
Doo-Dah
Doo-Dah is a quirky, affectionate nickname used by locals to refer to the city of Wichita, Kansas.
-
D.
Denguin
Denguin is a small commune in southwestern France, located in the Pyrénées-Atlantiques department in the Nouvelle-Aquitaine region.
-
E.
Boolaroo
Boolaroo is a suburb in the City of Lake Macquarie in New South Wales, Australia, historically known for its industrial activities and proximity to Cockle Creek and Lake Macquarie.
- 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_69ca848091c48190bc313d6620d09555 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd99aece1081908287e03106de020f |
completed | April 1, 2026, 10:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1615d093c8190940037e9e0842db5 |
completed | April 4, 2026, 7:07 p.m. |
Created at: March 30, 2026, 8:05 p.m.