Triple
T19180941
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pam Sheyne |
E469569
|
entity |
| Predicate | coWriterWith |
P7870
|
FINISHED |
| Object | David Frank |
—
|
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: David Frank | Statement: [Pam Sheyne, coWriterWith, David Frank]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: David Frank Context triple: [Pam Sheyne, coWriterWith, David Frank]
-
A.
David Frank
chosen
David Frank is a music producer best known for his work on Christina Aguilera’s hit single "Genie in a Bottle."
-
B.
Dan Frank
Dan Frank was an influential American book editor known for shaping contemporary literary fiction and nonfiction during his long tenure at major publishing houses.
-
C.
David Victor
David Victor was an American television producer and writer best known for creating the popular medical drama series "Marcus Welby, M.D."
-
D.
Dennis Balthaser
Dennis Balthaser is a UFO researcher and author best known for his investigations into the Roswell incident and his involvement with the International UFO Museum and Research Center.
-
E.
David Michael Frank
David Michael Frank is an American composer best known for his work on film and television scores.
- 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_69d8dd09d5a081909ae43c286651ae5a |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5f61be86c81908710341262e911cd |
completed | April 20, 2026, 9:47 a.m. |
Created at: April 10, 2026, 12:07 p.m.