Triple
T1567859
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Uruguay River |
E33471
|
entity |
| Predicate | hasCityOnBank |
P7935
|
FINISHED |
| Object | Gualeguaychú |
E181906
|
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: Gualeguaychú | Statement: [Uruguay River, hasCityOnBank, Gualeguaychú]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gualeguaychú Context triple: [Uruguay River, hasCityOnBank, Gualeguaychú]
-
A.
Gualeguaychú
chosen
Gualeguaychú is a city in eastern Argentina known for its vibrant Carnival celebrations and riverside tourism.
-
B.
Comodoro Rivadavia
Comodoro Rivadavia is a coastal city in southern Argentina known as a key oil industry hub and one of the main urban centers of Patagonia.
-
C.
San Miguel de Tucumán
San Miguel de Tucumán is a historic city in northwest Argentina known as the birthplace of the country’s independence, where the 1816 declaration was signed.
-
D.
Junín
Junín is a central highland region of Peru known for its Andean landscapes, rich mining and agricultural activities, and historical role in Peru’s independence.
-
E.
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.
- 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_69a885f11b048190935025a035302715 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a908a0314c8190a5ce3e32dd9035db |
completed | March 5, 2026, 4:37 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad797d8c68819093fb2bcae0a08698 |
completed | March 8, 2026, 1:28 p.m. |
Created at: March 4, 2026, 7:27 p.m.