Triple
T23189145
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | L'Wren Scott |
E579681
|
entity |
| Predicate | clientele |
P481
|
FINISHED |
| Object | Penélope Cruz |
—
|
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: Penélope Cruz | Statement: [L'Wren Scott, clientele, Penélope Cruz]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Penélope Cruz Context triple: [L'Wren Scott, clientele, Penélope Cruz]
-
A.
Penélope Cruz
chosen
Penélope Cruz is an acclaimed Spanish actress known for her versatile performances in both European and Hollywood cinema, including collaborations with director Pedro Almodóvar and roles in films such as "Vicky Cristina Barcelona."
-
B.
Paz Vega
Paz Vega is a Spanish actress known for her roles in films such as "Sex and Lucía," "Spanglish," and various international productions.
-
C.
Mónica Bardem
Mónica Bardem is a Spanish actress and member of the Bardem family, known for her work in film and television.
-
D.
Kate del Castillo
Kate del Castillo is a Mexican actress best known internationally for her leading roles in telenovelas and the crime drama series "La Reina del Sur."
-
E.
Pilar Bardem
Pilar Bardem was a Spanish actress and prominent member of the Bardem acting family, known for her extensive film and television career and her activism.
- 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_69e245ff8000819090d12008805315b7 |
completed | April 17, 2026, 2:38 p.m. |
| NER | Named-entity recognition | batch_69f18fd592248190a7e705c554885cd1 |
completed | April 29, 2026, 4:57 a.m. |
Created at: April 17, 2026, 4:05 p.m.