Triple
T8486336
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | A Most Violent Year |
E200840
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object | Elyes Gabel |
E732754
|
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: Elyes Gabel | Statement: [A Most Violent Year, starring, Elyes Gabel]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Elyes Gabel Context triple: [A Most Violent Year, starring, Elyes Gabel]
-
A.
Elyes Gabel
chosen
Elyes Gabel is a British actor known for roles in series such as "Game of Thrones," "Scorpion," and various UK television dramas.
-
B.
Safy Boutella
Safy Boutella is an Algerian musician and composer known for his influential role in modern Algerian music and film scores.
-
C.
Omar Sy
Omar Sy is a French actor and comedian best known internationally for his breakout role in the film "The Intouchables" and subsequent work in movies like "Jurassic World" and the series "Lupin."
-
D.
Saïd Taghmaoui
Saïd Taghmaoui is a French-American actor and screenwriter known for his breakout role in the film "La Haine" and numerous international performances in both European and Hollywood productions.
-
E.
Rami Nassar
Rami Nassar is a technology and innovation leader known for his work in digital strategy, product development, and emerging technologies.
- 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_69ca831d7b148190a6e32c1de43ab13b |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe53c4d608190a766c0e919a4b96f |
completed | March 31, 2026, 3:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ce3a45e30c8190838ac499bbc66fbd |
completed | April 2, 2026, 9:43 a.m. |
Created at: March 30, 2026, 6:13 p.m.