Triple
T10691050
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Riachuelo River |
E252007
|
entity |
| Predicate | passesThrough |
P225
|
FINISHED |
| Object | Avellaneda |
E329768
|
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: Avellaneda | Statement: [Riachuelo River, passesThrough, Avellaneda]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Avellaneda Context triple: [Riachuelo River, passesThrough, Avellaneda]
-
A.
Avellaneda
chosen
Avellaneda is a city in the Buenos Aires Province of Argentina, known as an important industrial and port center within the Greater Buenos Aires metropolitan area.
-
B.
Montalva
Montalva is a Spanish-language surname notably associated with Chilean president Eduardo Frei Montalva.
-
C.
Almagro
Almagro is a traditional middle-class neighborhood in central Buenos Aires, Argentina, known for its historic tango culture, cafes, and densely populated residential streets.
-
D.
Almagro
Almagro is a Spanish surname borne by various notable figures, including politicians, athletes, and artists from Spanish-speaking countries.
-
E.
Moncalvo
Moncalvo is a small historic town in Italy’s Piedmont region, known as one of the country’s smallest cities and for its wine and truffle production.
- 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_69d6aa5bd7c08190a816e733b4045c23 |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d6fd3705788190bcbdef93b4c5f574 |
completed | April 9, 2026, 1:13 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d988a59d6c8190a0e170acfb3af6da |
completed | April 10, 2026, 11:32 p.m. |
Created at: April 8, 2026, 9:11 p.m.