Triple
T19795916
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Andrés Bello |
E475539
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Andrés |
—
|
NE NERFINISHED |
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: Andrés | Statement: [Andrés Bello, givenName, Andrés]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Andrés Context triple: [Andrés Bello, givenName, Andrés]
-
A.
Andrés
chosen
Andrés is a Spanish given name commonly used as the equivalent of Andrew.
-
B.
Sebastián
Sebastián is a masculine given name of Spanish origin commonly used in Spanish-speaking countries.
-
C.
Sebastián
Sebastián is a renowned Mexican sculptor celebrated for his monumental geometric public artworks.
-
D.
Jorge
Jorge is a central figure in Eça de Queirós’s realist novel "O Primo Basílio," embodying the bourgeois husband whose domestic life is upended by his wife’s adulterous affair.
-
E.
Jorge
Jorge is a masculine given name of Spanish and Portuguese origin, equivalent to George in English.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8e51b014081908b263e167370529a |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e653c659088190928fa4c9264135d3 |
completed | April 20, 2026, 4:26 p.m. |
Created at: April 10, 2026, 1:49 p.m.