Triple
T15469875
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Coffee Town |
E372130
|
entity |
| Predicate | castMember |
P1668
|
FINISHED |
| Object | Ben Schwartz |
E547340
|
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: Ben Schwartz | Statement: [Coffee Town, castMember, Ben Schwartz]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ben Schwartz Context triple: [Coffee Town, castMember, Ben Schwartz]
-
A.
Ben Schwartz
chosen
Ben Schwartz is an American actor, comedian, and voice performer known for roles in projects like Parks and Recreation and for voicing animated characters in films and television.
-
B.
Ben Schwarz
Ben Schwarz is a German local politician who serves as the mayor of the municipality of Georgensgmünd in Bavaria.
-
C.
Michael Ian Schwartz
Michael Ian Schwartz, better known as Michael Ian Black, is an American comedian, actor, writer, and director recognized for his work on shows like "The State" and "Stella."
-
D.
Seth Gabel
Seth Gabel is an American actor known for his roles in television series such as "Fringe," "Salem," and "Nip/Tuck."
-
E.
Eric Bauza
Eric Bauza is a Canadian voice actor and comedian best known for portraying iconic animated characters in modern Looney Tunes productions.
- 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_69d85cc8bd308190886949510b42e764 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e03f6b49788190b270fdfe92646842 |
completed | April 16, 2026, 1:46 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff677ef27c81909fd160205b71ca55 |
completed | May 9, 2026, 4:57 p.m. |
Created at: April 10, 2026, 3:33 a.m.