Triple
T19033656
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vilnius County |
E465807
|
entity |
| Predicate | hasTown |
P847
|
FINISHED |
| Object | Švenčionys |
—
|
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: Švenčionys | Statement: [Vilnius County, hasTown, Švenčionys]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Švenčionys Context triple: [Vilnius County, hasTown, Švenčionys]
-
A.
Švenčionys
chosen
Švenčionys is a small historic town in eastern Lithuania known for its multicultural past and former Jewish community.
-
B.
Radviliškis
Radviliškis is a town in northern Lithuania known as a regional railway hub and administrative center within Šiauliai County.
-
C.
Vilkaviškis
Vilkaviškis is a town in southwestern Lithuania known as an administrative and historical center of the surrounding agricultural region.
-
D.
Joniškis
Joniškis is a small town in northern Lithuania known for its historic architecture and cultural heritage, including well-preserved synagogues.
-
E.
Zarasai
Zarasai is a small town in northeastern Lithuania known for its lakes and scenic natural surroundings.
- 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_69d8dd0359648190bc2a9202c5cf29d2 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5d741cabc8190900e12265ad269f8 |
completed | April 20, 2026, 7:35 a.m. |
Created at: April 10, 2026, 12:02 p.m.