Triple
T14411734
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maribel Verdú |
E357343
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Rollán |
E357343
|
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: Rollán | Statement: [Maribel Verdú, familyName, Rollán]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rollán Context triple: [Maribel Verdú, familyName, Rollán]
-
A.
Rollán
chosen
Rollán is the Spanish family name of actress Maribel Verdú, known for her prominent roles in Spanish and international cinema.
-
B.
Rolando
Rolando is a masculine given name, commonly used in Romance-language countries, that is a variant of the name Orlando/Roland.
-
C.
Guillermón
Guillermón was the popular nickname of Cuban independence general Guillermón Moncada, a prominent Afro-Cuban military leader in the wars against Spanish colonial rule.
-
D.
Blasco
Blasco is a masculine given name of Spanish origin, historically borne by notable figures such as colonial administrators and writers.
-
E.
Baltasar
Baltasar is a variant of the name Belshazzar, historically associated with the last king of Babylon mentioned in the biblical Book of Daniel.
- 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_69d82793421c8190861eb0e673b085de |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de90c9b3448190aec1608836a5e913 |
completed | April 14, 2026, 7:08 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd55269d8c81909592277741a93db6 |
completed | May 8, 2026, 3:14 a.m. |
Created at: April 10, 2026, 1:17 a.m.