Triple
T2461706
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fast & Furious |
E54547
|
entity |
| Predicate | stars |
P1956
|
FINISHED |
| Object | Gal Gadot |
E199710
|
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: Gal Gadot | Statement: [Fast & Furious, stars, Gal Gadot]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gal Gadot Context triple: [Fast & Furious, stars, Gal Gadot]
-
A.
Gal Gadot
chosen
Gal Gadot is an Israeli actress and model best known internationally for portraying Wonder Woman in the DC Extended Universe films.
-
B.
Ruby Rose
Ruby Rose is an Australian model, DJ, and actress known for her androgynous style and roles in action films and television series such as "Orange Is the New Black."
-
C.
Margot Robbie
Margot Robbie is an Australian actress and producer known for her versatile performances in films such as "The Wolf of Wall Street," "I, Tonya," and "Barbie."
-
D.
Scarlett Johansson
Scarlett Johansson is an American actress known for her versatile film roles, including major parts in the Marvel Cinematic Universe and acclaimed performances in both independent and blockbuster movies.
-
E.
Dakota Johnson
Dakota Johnson is an American actress best known for starring as Anastasia Steele in the film adaptation of the erotic romance novel "Fifty Shades of Grey" and its sequels.
- 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_69ab49dee84c819096b50a0049c347ac |
completed | March 6, 2026, 9:40 p.m. |
| NER | Named-entity recognition | batch_69abd11c47408190b10c7f6a151f2db2 |
completed | March 7, 2026, 7:17 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69aef0d2b2748190b12611863d8bf4ad |
completed | March 9, 2026, 4:09 p.m. |
Created at: March 6, 2026, 9:44 p.m.