Triple
T23023429
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mad Love (TV series) |
E573231
|
entity |
| Predicate | createdBy |
P806
|
FINISHED |
| Object | Matt Tarses |
—
|
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: Matt Tarses | Statement: [Mad Love (TV series), createdBy, Matt Tarses]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Matt Tarses Context triple: [Mad Love (TV series), createdBy, Matt Tarses]
-
A.
Matt Tarses
chosen
Matt Tarses is an American television writer and producer known for his work on series such as Scrubs and The Goldbergs.
-
B.
Jay Tarses
Jay Tarses is an American television writer, producer, and actor known for his work on acclaimed comedy series such as "The Bob Newhart Show" and "Buffalo Bill."
-
C.
Matt Tauber
Matt Tauber is a film producer known for his work on the drama movie "Meadowland."
-
D.
Matthew Shafer
Matthew Shafer is an American writer known for his work on the animated series "Cowboy Bebop" and related projects.
-
E.
Matthew Shafer
Matthew Shafer, better known by his stage name Uncle Kracker, is an American singer-songwriter and musician recognized for his blend of rock, country, and pop influences.
- 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_69e245b821008190b0e09cb02092aae1 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f1847b86688190b678d0d09ecd3c3d |
completed | April 29, 2026, 4:09 a.m. |
Created at: April 17, 2026, 3:52 p.m.