Triple
T20183526
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Anaconda (1997 film) |
E492792
|
entity |
| Predicate | starredActor |
P5563
|
FINISHED |
| Object | Jonathan Hyde |
—
|
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: Jonathan Hyde | Statement: [Anaconda (1997 film), starredActor, Jonathan Hyde]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jonathan Hyde Context triple: [Anaconda (1997 film), starredActor, Jonathan Hyde]
-
A.
Jonathan Hyde
chosen
Jonathan Hyde is an English-Australian actor known for his roles in films like "Titanic," "Jumanji," and "The Mummy," as well as extensive work in television, theatre, and voice acting.
-
B.
Warren Pleece
Warren Pleece is a British comic book artist and illustrator known for his distinctive work on graphic novels and series such as Incognegro.
-
C.
Richard Marden
Richard Marden was a British film editor known for his work on notable mid-20th-century films, including adaptations of classic literature.
-
D.
Daniel Hyde
Daniel Hyde is a British choral conductor and organist known for his leadership of prestigious cathedral and collegiate choirs, including King’s College, Cambridge.
-
E.
Michael Craig
Michael Craig is a British actor and screenwriter known for his work in mid-20th-century film and television, including roles in dramas and thrillers.
- 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_69da6268a034819081cbd9ea5a1c9475 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e668f068748190a0941e98ef5afd59 |
completed | April 20, 2026, 5:57 p.m. |
Created at: April 11, 2026, 11:36 p.m.