Triple
T18282253
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Varniai Cathedral |
E437891
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Varniai |
—
|
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: Varniai | Statement: [Varniai Cathedral, locatedIn, Varniai]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Varniai Context triple: [Varniai Cathedral, locatedIn, Varniai]
-
A.
Varniai
chosen
Varniai is a historic town in Lithuania that once served as a key political and religious center of the Samogitian region.
-
B.
Velnias
Velnias is a chthonic deity in Baltic paganism associated with the underworld, the dead, and often trickster-like or demonic qualities.
-
C.
Visaginas
Visaginas is a town in northeastern Lithuania known for its Soviet-era origins and proximity to the now-decommissioned Ignalina Nuclear Power Plant.
-
D.
Vilkaviškis
Vilkaviškis is a town in southwestern Lithuania known as an administrative and historical center of the surrounding agricultural region.
-
E.
Radviliškis
Radviliškis is a town in northern Lithuania known as a regional railway hub and administrative center within Šiauliai County.
- 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_69d8b914530c8190b4474d862a2b2a1b |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e50057c5c881909fcda72f4a98c8c3 |
completed | April 19, 2026, 4:18 p.m. |
Created at: April 10, 2026, 10:35 a.m.