Triple
T10031007
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Circuital |
E204850
|
entity |
| Predicate | performer |
P1363
|
FINISHED |
| Object | Carl Broemel |
E783585
|
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: Carl Broemel | Statement: [Circuital, performer, Carl Broemel]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Carl Broemel Context triple: [Circuital, performer, Carl Broemel]
-
A.
Carl Broemel
chosen
Carl Broemel is an American guitarist, singer-songwriter, and multi-instrumentalist best known as a longtime member of the rock band My Morning Jacket.
-
B.
Ray Heindorf
Ray Heindorf was an American composer, arranger, and musical director best known for his work on numerous Hollywood film scores during the mid-20th century.
-
C.
Greg Beeman
Greg Beeman is an American television director and producer known for his work on genre series such as "Falling Skies," "Heroes," and "Smallville."
-
D.
Kevin Nolting
Kevin Nolting is an American film editor best known for his work on Pixar animated features, including the Academy Award-winning film "Up."
-
E.
Kevin Biegel
Kevin Biegel is an American television writer and producer best known for co-creating the sitcom Cougar Town and working on shows like Scrubs and Enlisted.
- 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_69ca834d77188190ad645e33e8ca3200 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cdcde7ec088190845656cc2529c771 |
completed | April 2, 2026, 2:01 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69deafff4b8c819099d47b48773c3629 |
completed | April 14, 2026, 9:22 p.m. |
Created at: March 30, 2026, 8:54 p.m.