Triple
T4802291
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Carmen de Patagones |
E106862
|
entity |
| Predicate | locatedOpposite |
P3232
|
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: [Carmen de Patagones, locatedOpposite, Viedma]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Viedma Context triple: [Carmen de Patagones, locatedOpposite, 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.
Viljandi
Viljandi is a historic town in southern Estonia known for its medieval castle ruins, rich cultural life, and annual folk music festival.
-
C.
Pärnu
Pärnu is a coastal city in southwestern Estonia known as a popular summer resort and spa destination on the Baltic Sea.
-
D.
Jõepere
Jõepere is a village in Estonia known as the birthplace of the national writer Friedrich Reinhold Kreutzwald.
-
E.
Kuressaare
Kuressaare is the main town on Estonia’s Saaremaa island, known for its well-preserved medieval castle and seaside spa resort atmosphere.
- 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_69bd43f6a1e08190bf0a372bfc336ee5 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6c42113081908824f3608e65cbff |
completed | March 20, 2026, 3:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be4400103c8190a5417fe75fb50f81 |
completed | March 21, 2026, 7:08 a.m. |
Created at: March 20, 2026, 1:23 p.m.