Triple
T18685227
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Idol |
E456842
|
entity |
| Predicate | castMember |
P1668
|
FINISHED |
| Object | Dan Levy |
—
|
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: Dan Levy | Statement: [The Idol, castMember, Dan Levy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dan Levy Context triple: [The Idol, castMember, Dan Levy]
-
A.
Dan Levy
chosen
Dan Levy is a Canadian actor, writer, and producer best known as the co-creator and star of the acclaimed television series "Schitt's Creek."
-
B.
Dan Levy
Dan Levy is a French multi-instrumentalist, composer, and producer best known as one half of the indie pop/rock duo The Dø.
-
C.
Daniel Levy
Daniel Levy is a British businessman best known for his long-serving and influential role as chairman of Premier League football club Tottenham Hotspur.
-
D.
Lucas Pegg
Lucas Pegg is the protagonist of the science fiction story "Threshold," around whom the central narrative and character development revolve.
-
E.
Mathew Baynton
Mathew Baynton is an English actor, writer, comedian, and musician best known for his work on "Horrible Histories," "Ghosts," and various British television comedies.
- 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_69d8d391eb488190ac2e9abf5bf255e4 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e55b2c58188190b906c9ab080a76ff |
completed | April 19, 2026, 10:46 p.m. |
Created at: April 10, 2026, 11:49 a.m.