Triple
T22891019
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Knight and Day |
E568039
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object | Jordi Mollà |
—
|
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: Jordi Mollà | Statement: [Knight and Day, starring, Jordi Mollà]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jordi Mollà Context triple: [Knight and Day, starring, Jordi Mollà]
-
A.
Jordi Mollà
chosen
Jordi Mollà is a Spanish actor, director, and artist known for his intense character roles in both European cinema and Hollywood films such as "Blow" and "Bad Boys II."
-
B.
Jordi Gali
Jordi Galí is a prominent Spanish macroeconomist known for his influential work on New Keynesian economics and monetary policy.
-
C.
Juan Dalmau
Juan Dalmau is a Puerto Rican lawyer and politician best known as a leading figure and former gubernatorial candidate of the Puerto Rican Independence Party.
-
D.
Quim Salvi
Quim Salvi is a Spanish academic and university administrator who serves as rector of the University of Girona in Catalonia.
-
E.
Queralt Castellet
Queralt Castellet is a Spanish professional snowboarder and multiple-time Olympian best known for competing in the halfpipe event at the Winter Olympic Games.
- 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_69e2458c23ec81908fa2570692c6614f |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f17fc59e108190a22f90c2439830fb |
completed | April 29, 2026, 3:49 a.m. |
Created at: April 17, 2026, 3:40 p.m.