Triple
T10367770
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Afterlife |
E244298
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object | Michele Buck |
E513652
|
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: Michele Buck | Statement: [Afterlife, producer, Michele Buck]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Michele Buck Context triple: [Afterlife, producer, Michele Buck]
-
A.
Michele Buck
chosen
Michele Buck is a British television producer best known for her work on popular drama series such as "Agatha Christie's Marple" and "Poirot."
-
B.
Michele Gossett
Michele Gossett is known as the wife of American actor Robert Gossett.
-
C.
Dennis McAuliffe
Dennis McAuliffe is a journalist and author known for his work on Native American issues and his book investigating the mysterious death of his Osage grandmother.
-
D.
Jim Mullen
Jim Mullen is a Scottish jazz guitarist renowned for his soulful, groove-oriented playing and collaborations with leading British jazz and fusion artists.
-
E.
Michael Tucker
Michael Tucker is an American actor best known for his work in film, television, and theater, including roles in projects like the Woody Allen film "Radio Days" and the TV series "L.A. Law."
- 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_69d381b3e328819094b23b8edcd29b5a |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4e97106448190a075948e63184f47 |
completed | April 7, 2026, 11:24 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d79546b078819089dec7628c95a681 |
completed | April 9, 2026, 12:02 p.m. |
Created at: April 6, 2026, noon