Triple
T21961642
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alexis Argüello |
E542344
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Argüello |
—
|
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: Argüello | Statement: [Alexis Argüello, familyName, Argüello]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Argüello Context triple: [Alexis Argüello, familyName, Argüello]
-
A.
Argüello
chosen
Argüello is a Spanish-language surname of likely Iberian or Latin American origin borne by various notable individuals.
-
B.
Argüelles
Argüelles is a Madrid Metro station serving the Argüelles neighborhood, providing an interchange between several central metro lines.
-
C.
Montalva
Montalva is a Spanish-language surname notably associated with Chilean president Eduardo Frei Montalva.
-
D.
Aranguez
Aranguez is a residential and commercial neighborhood in the San Juan–Laventille region of Trinidad and Tobago, known for its agricultural lands and proximity to Port of Spain.
-
E.
Montúfar
Montúfar is a Spanish-origin surname historically associated with notable figures in Latin American colonial and independence-era history.
- 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_69e0c47fab1081908dc74a6545dbb051 |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f124572738819098cc669aafa53cc6 |
completed | April 28, 2026, 9:19 p.m. |
Created at: April 16, 2026, 8 p.m.