Triple
T14519869
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | A Fistful of Dollars |
E340622
|
entity |
| Predicate | productionCompany |
P490
|
FINISHED |
| Object | Jolly Film |
E911668
|
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: Jolly Film | Statement: [A Fistful of Dollars, productionCompany, Jolly Film]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jolly Film Context triple: [A Fistful of Dollars, productionCompany, Jolly Film]
-
A.
Jolly Film
chosen
Jolly Film is an Italian film production company best known for backing Sergio Leone’s influential Spaghetti Westerns, including the Dollars Trilogy.
-
B.
Geria Film
Geria Film is a film production company known for producing the movie "Fedora."
-
C.
Lolafilms
Lolafilms is a Spanish film production company known for backing prominent Spanish-language cinema, including acclaimed features from the 1990s and 2000s.
-
D.
Dohafilms
Dohafilms is a film production company known for helping produce the 2014 animated adaptation of Kahlil Gibran’s "The Prophet."
-
E.
Googly Films
Googly Films is a film production company best known for producing the visually striking fantasy drama "The Fall" (2006).
- 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_69d822d9c0408190b9a2b3643e58bb4d |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69de9a70b15c81908773633e989ef704 |
completed | April 14, 2026, 7:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd7a4b71688190ae9ebccdc81d09f8 |
completed | May 8, 2026, 5:53 a.m. |
Created at: April 10, 2026, 1:22 a.m.