Triple
T7049620
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Green Mansions |
E163730
|
entity |
| Predicate | director |
P255
|
FINISHED |
| Object | Mel Ferrer |
E172353
|
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: Mel Ferrer | Statement: [Green Mansions, director, Mel Ferrer]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mel Ferrer Context triple: [Green Mansions, director, Mel Ferrer]
-
A.
Mel Ferrer
chosen
Mel Ferrer was an American actor, director, and producer known for his work in classic Hollywood films and his marriage to Audrey Hepburn.
-
B.
José Ferrer
José Ferrer was a Puerto Rican-born actor and director renowned for his Oscar-winning performance in "Cyrano de Bergerac" and his distinguished career on stage and screen.
-
C.
Fernando Lamas
Fernando Lamas was an Argentine-American actor and director known for his suave, romantic leading roles in Hollywood films of the 1950s.
-
D.
Victor Jory
Victor Jory was a Canadian-born American character actor known for his distinctive deep voice and frequent portrayals of villains in film, television, and theater during the mid-20th century.
-
E.
Henry Silva
Henry Silva was an American character actor known for his intense, often villainous roles in films such as "The Manchurian Candidate" and numerous crime and action movies from the 1950s through the 1990s.
- 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_69c6885f598c8190b6b6495c59d8d962 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6e24d5e8c8190b37e56107e6da8ab |
completed | March 27, 2026, 8:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7a316374c81908deeb60b8f58a3c8 |
completed | March 28, 2026, 9:44 a.m. |
Created at: March 27, 2026, 2:37 p.m.