Triple
T16893654
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dzūkija |
E424239
|
entity |
| Predicate | includesCity |
P3207
|
FINISHED |
| Object | Druskininkai |
E613767
|
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: Druskininkai | Statement: [Dzūkija, includesCity, Druskininkai]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Druskininkai Context triple: [Dzūkija, includesCity, Druskininkai]
-
A.
Druskininkai
chosen
Druskininkai is a well-known spa and resort town in southern Lithuania, famous for its mineral springs and wellness tourism.
-
B.
Švenčionys
Švenčionys is a small historic town in eastern Lithuania known for its multicultural past and former Jewish community.
-
C.
Rokiškis
Rokiškis is a town in northeastern Lithuania known for its well-preserved manor, historic architecture, and role as a regional cultural center.
-
D.
Radviliškis
Radviliškis is a town in northern Lithuania known as a regional railway hub and administrative center within Šiauliai County.
-
E.
Joniškis
Joniškis is a small town in northern Lithuania known for its historic architecture and cultural heritage, including well-preserved synagogues.
- 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_69d889da3e8c8190a2b118f383f0beac |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e3bbc6b97c8190b18aca477d6ef647 |
completed | April 18, 2026, 5:13 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a01954069e0819087fab0a782a83f39 |
completed | May 11, 2026, 8:37 a.m. |
Created at: April 10, 2026, 5:29 a.m.