Triple
T10662052
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Governor of Mendoza |
E251249
|
entity |
| Predicate | seat |
P75
|
FINISHED |
| Object | Mendoza, Argentina |
E251243
|
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: Mendoza, Argentina | Statement: [Governor of Mendoza, seat, Mendoza, Argentina]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mendoza, Argentina Context triple: [Governor of Mendoza, seat, Mendoza, Argentina]
-
A.
Mendoza
chosen
Mendoza is a major city in western Argentina known as a gateway to the Andes and the country’s premier wine-producing region.
-
B.
Mendoza
Mendoza is a common Spanish-language surname borne by numerous notable individuals across the Spanish-speaking world.
-
C.
Santa Fe, Argentina
Santa Fe, Argentina is a major river port city and the capital of Santa Fe Province, located in northeastern Argentina along the Paraná and Salado rivers.
-
D.
San Martín, Mendoza
San Martín, Mendoza is a city in Argentina’s Mendoza Province known for its agricultural production, particularly vineyards and wineries, within the country’s main wine-growing region.
-
E.
Colón, Argentina
Colón, Argentina is a riverside city in Entre Ríos Province known for its beaches on the Uruguay River, hot springs, and role as a popular tourist gateway to nearby natural attractions.
- 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_69d6aa5b0d2881909584b20efc5877f0 |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d6e018d1e881909b8e62682104e842 |
completed | April 8, 2026, 11:09 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69de8461e0448190b801a0ed128d9dcb |
completed | April 14, 2026, 6:16 p.m. |
Created at: April 8, 2026, 9:08 p.m.