Triple
T899716
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Río Negro |
E19418
|
entity |
| Predicate | separates |
P1175
|
FINISHED |
| Object | Viedma |
E106861
|
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: Viedma | Statement: [Río Negro, separates, Viedma]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Viedma Context triple: [Río Negro, separates, Viedma]
-
A.
Viedma
chosen
Viedma is a city in northern Patagonia and one of the oldest settlements in Argentina, serving as the capital of Río Negro Province.
-
B.
Vianen
Vianen is a historic Dutch town known for its medieval city center and location near major rivers in the western Netherlands.
-
C.
Lielupe
Lielupe is a major river in central Latvia that flows into the Gulf of Riga and is known for its wide floodplain and role in regional agriculture and transport.
-
D.
Tartu
Tartu is Estonia’s second-largest city and a historic cultural and intellectual center, best known as the country’s main university town.
-
E.
Hiiumaa
Hiiumaa is Estonia’s second-largest island, located in the Baltic Sea and known for its unspoiled nature, lighthouses, and quiet rural landscapes.
- 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_69a4939e889c8190ac148b3ac1a7f90b |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4ad4162848190aa2787b2fa3e6575 |
completed | March 1, 2026, 9:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a7cf5a4118819086035d6e250a53cc |
completed | March 4, 2026, 6:21 a.m. |
Created at: March 1, 2026, 7:39 p.m.