Triple
T17399651
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mike & Molly |
E423052
|
entity |
| Predicate | composer |
P1361
|
FINISHED |
| Object | Grant Geissman |
—
|
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: Grant Geissman | Statement: [Mike & Molly, composer, Grant Geissman]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Grant Geissman Context triple: [Mike & Molly, composer, Grant Geissman]
-
A.
Grant Geissman
chosen
Grant Geissman is an American jazz and studio guitarist and composer known for his solo work and contributions to television and film scores.
-
B.
Bill Geisslinger
Bill Geisslinger is an American actor known for his work in theater and television and for his former marriage to actress Annette O'Toole.
-
C.
Kevin Strickland
Kevin Strickland is an American man whose decades-long wrongful murder conviction and eventual exoneration drew national attention to flaws in the U.S. criminal justice system.
-
D.
Ian Megibben
Ian Megibben is a cinematographer best known for his work on the animated film "Finding Dory."
-
E.
Ian Megibben
Ian Megibben is a cinematographer best known for his work on the animated feature film "Lightyear."
- 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_69d889d710288190bf0f4762801fefae |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e43ac0596481908c400916d5c1b971 |
completed | April 19, 2026, 2:15 a.m. |
Created at: April 10, 2026, 5:45 a.m.