Triple
T5182665
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Úrsula Corberó |
E116957
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Úrsula Corberó |
E116957
|
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: Úrsula Corberó | Statement: [Úrsula Corberó, name, Úrsula Corberó]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Úrsula Corberó Context triple: [Úrsula Corberó, name, Úrsula Corberó]
-
A.
Úrsula Corberó
chosen
Úrsula Corberó is a Spanish actress best known internationally for her role as Tokyo in the hit television series "Money Heist."
-
B.
Ana de Armas
Ana de Armas is a Cuban-Spanish actress known for her breakout roles in films such as "Blade Runner 2049," "Knives Out," and "Blonde."
-
C.
Elena Anaya
Elena Anaya is a Spanish actress known for her roles in both European cinema and Hollywood productions, including prominent performances in films like "The Skin I Live In."
-
D.
Diane Guerrero
Diane Guerrero is an American actress and author best known for her roles in the television series "Orange Is the New Black" and "Jane the Virgin," as well as her voice work in animated films.
-
E.
Marisa del Toro
Marisa del Toro is one of the children of acclaimed Mexican filmmaker Guillermo del Toro.
- 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_69bd446140f08190becb93c61158f27f |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd799d50388190bf2b7dfdd90949e9 |
completed | March 20, 2026, 4:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bed95b2900819082b534e27484171e |
completed | March 21, 2026, 5:46 p.m. |
Created at: March 20, 2026, 1:46 p.m.