Triple
T19394316
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Casa Natal de San Martín |
E485147
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Yapeyú |
—
|
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: Yapeyú | Statement: [Casa Natal de San Martín, locatedIn, Yapeyú]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Yapeyú Context triple: [Casa Natal de San Martín, locatedIn, Yapeyú]
-
A.
Yapeyú
chosen
Yapeyú is a small town in northeastern Argentina, historically notable as the birthplace of independence leader José de San Martín.
-
B.
Cosquín
Cosquín is a town in central Argentina best known for hosting one of the country’s most important annual folk music festivals.
-
C.
Panguipulli
Panguipulli is a scenic town in southern Chile known for its lakeside setting, surrounding volcanoes, and role as a gateway to the Andean lake district.
-
D.
Cuencamé
Cuencamé is a municipality and town in the Mexican state of Durango, historically part of the colonial province of Nueva Vizcaya.
-
E.
Vizcaína
Vizcaína was one of the ships in Christopher Columbus’s fourth voyage to the Americas in the early 16th century.
- 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_69d8e8d5162481909db12435d9535c1a |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e61b47630881909ba390888b8779f6 |
completed | April 20, 2026, 12:25 p.m. |
Created at: April 10, 2026, 1:36 p.m.