Triple
T3433036
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maribel Verdú |
E72383
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Maribel Verdú |
E72383
|
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: Maribel Verdú | Statement: [Maribel Verdú, name, Maribel Verdú]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Maribel Verdú Context triple: [Maribel Verdú, name, Maribel Verdú]
-
A.
Maribel Verdú
chosen
Maribel Verdú is a Spanish actress acclaimed for her work in films such as "Pan’s Labyrinth" and "Y Tu Mamá También."
-
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.
Emilia Gorriarán
Emilia Gorriarán was the mother of Cuban revolutionary figure Camilo Cienfuegos.
-
D.
Pilar Roldán
Pilar Roldán is a Mexican fencer best known for taking the Olympic Oath for athletes and winning a silver medal in women's foil at the 1968 Mexico City Games.
-
E.
Inés García
Inés García was the wife of Mexican general and politician Antonio López de Santa Anna, associated with his personal and political life during 19th-century Mexico.
- 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_69ad85ae14308190bcbc25cfa0246c0b |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb9c077d48190bee40795cab3e422 |
completed | March 8, 2026, 6:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b3547d3f4c8190bc6811398bd8f080 |
completed | March 13, 2026, 12:04 a.m. |
Created at: March 8, 2026, 3:15 p.m.