Triple
T20952875
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kėdainiai County |
E516022
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Kėdainiai |
—
|
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: Kėdainiai | Statement: [Kėdainiai County, contains, Kėdainiai]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kėdainiai Context triple: [Kėdainiai County, contains, Kėdainiai]
-
A.
Kėdainiai
chosen
Kėdainiai is a historic city in central Lithuania known for its well-preserved old town and multicultural heritage.
-
B.
Kuršėnai
Kuršėnai is a town in northern Lithuania known for its pottery traditions and location along the Venta River.
-
C.
Kelmė
Kelmė is a small town in northern Lithuania known as the administrative center of Kelmė District Municipality and for its historic manor and surrounding rural landscapes.
-
D.
Karmėlava
Karmėlava is a Lithuanian town near Kaunas known for hosting Kaunas International Airport and serving as a local transport and residential hub.
-
E.
Švenčionys
Švenčionys is a small historic town in eastern Lithuania known for its multicultural past and former Jewish community.
- 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_69e0b4fcd678819087a304291f14330a |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6fadf85f88190924d3919b9e665e4 |
completed | April 21, 2026, 4:19 a.m. |
Created at: April 16, 2026, 1:27 p.m.