Triple
T20717196
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Minas Department |
E509201
|
entity |
| Predicate | hasSettlement |
P1068
|
FINISHED |
| Object | Varvarco |
—
|
NE NERFINISHED |
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: Varvarco | Statement: [Minas Department, hasSettlement, Varvarco]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Varvarco Context triple: [Minas Department, hasSettlement, Varvarco]
-
A.
Varvarco
chosen
Varvarco is a small town in Argentina’s Neuquén Province, known as a gateway to the Domuyo volcanic region and its surrounding Andean landscapes.
-
B.
Varvarin
Varvarin is a small town in central Serbia situated on the banks of the Velika Morava River.
-
C.
Vara
Vara is a short form of the female given name Varvara, commonly used in Slavic languages.
-
D.
Vara
Vara is a small locality and municipality in western Sweden known for its agricultural landscape and rural character.
-
E.
Vararuci
Vararuci is an ancient Indian scholar and grammarian traditionally credited with important contributions to the study and codification of Prakrit languages.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b4c40ad88190b81f77695366d328 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c1d2c57481909840945ffd3b0cc3 |
completed | April 21, 2026, 12:16 a.m. |
Created at: April 16, 2026, 12:16 p.m.