Triple
T13667656
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Death at a Funeral |
E327662
|
entity |
| Predicate | castMember |
P1668
|
FINISHED |
| Object | Peter Dinklage |
E292625
|
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: Peter Dinklage | Statement: [Death at a Funeral, castMember, Peter Dinklage]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Peter Dinklage Context triple: [Death at a Funeral, castMember, Peter Dinklage]
-
A.
Peter Dinklage
chosen
Peter Dinklage is an American actor best known for his Emmy-winning role as Tyrion Lannister in the television series "Game of Thrones."
-
B.
Robin Lord Taylor
Robin Lord Taylor is an American actor best known for his acclaimed portrayal of Oswald Cobblepot/The Penguin on the television series "Gotham."
-
C.
James Whishaw
James Whishaw is the twin brother of English actor Ben Whishaw.
-
D.
Ciarán Hinds
Ciarán Hinds is an Irish actor known for his versatile performances in film, television, and theatre, with notable roles in works such as "Rome," "There Will Be Blood," and "Game of Thrones."
-
E.
Michael Konyves
Michael Konyves is a Canadian screenwriter best known for adapting Mordecai Richler’s novel into the acclaimed film "Barney’s Version."
- 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_69d8076f1fa8819094664a59b55010df |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbc65832688190aea688fee0a7cbdb |
completed | April 12, 2026, 4:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f78b0cfe0c8190b0fe50931e9788cf |
completed | May 3, 2026, 5:51 p.m. |
Created at: April 9, 2026, 9:52 p.m.