Triple
T10660679
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pilar Bardem |
E251214
|
entity |
| Predicate | relative |
P37
|
FINISHED |
| Object | Carlos Bardem |
E252228
|
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: Carlos Bardem | Statement: [Pilar Bardem, relative, Carlos Bardem]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Carlos Bardem Context triple: [Pilar Bardem, relative, Carlos Bardem]
-
A.
Carlos Bardem
chosen
Carlos Bardem is a Spanish actor and writer known for his character roles in film and television and for being part of the prominent Bardem family in Spanish cinema.
-
B.
Rafael Bardem
Rafael Bardem was a Spanish film and stage actor active in the mid-20th century and a member of the prominent Bardem acting family.
-
C.
Bardem
Bardem is a prominent Spanish family name best known internationally through actors like Javier Bardem and his relatives in the Spanish film industry.
-
D.
Javier Bardem
Javier Bardem is an acclaimed Spanish actor known for his intense, versatile performances in films such as "No Country for Old Men," "Biutiful," and "Skyfall."
-
E.
Luis Tosar
Luis Tosar is a acclaimed Spanish actor known for his intense performances in films such as "Cell 211" and "Take My Eyes," which have earned him major national awards.
- 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_69d6aa5b0d2881909584b20efc5877f0 |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d6e017f97c8190b22765a6f1e6719d |
completed | April 8, 2026, 11:09 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69deb07626988190a46d8a54eda156f5 |
completed | April 14, 2026, 9:24 p.m. |
Created at: April 8, 2026, 9:08 p.m.