Triple
T3497172
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nicolás Guillén |
E73878
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Nicolás |
E77168
|
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: Nicolás | Statement: [Nicolás Guillén, givenName, Nicolás]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nicolás Context triple: [Nicolás Guillén, givenName, Nicolás]
-
A.
Nicolás
chosen
Nicolás is a masculine given name of Greek origin, commonly used in Spanish-speaking countries and derived from the name Nicholas, meaning "victory of the people."
-
B.
Mariano
Mariano is a masculine given name of Spanish and Portuguese origin, commonly used in various Spanish-speaking and Latin cultures.
-
C.
Enrique
Enrique is a Spanish given name equivalent to the English name Henry.
-
D.
Juan Antonio
Juan Antonio is a Spanish film director best known for works such as "The Orphanage," "The Impossible," and "A Monster Calls."
-
E.
Mauricio
Mauricio is a masculine given name, commonly used in Spanish- and Portuguese-speaking countries, derived from the Latin name Mauritius.
- 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_69ad85cdb6e48190a335d412b9194ed8 |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adbbd16c0081908f13535f459618d1 |
completed | March 8, 2026, 6:11 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b373d011c0819088245afe03be3c44 |
completed | March 13, 2026, 2:17 a.m. |
Created at: March 8, 2026, 3:18 p.m.