Triple
T16893655
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dzūkija |
E424239
|
entity |
| Predicate | includesCity |
P3207
|
FINISHED |
| Object | Varėna |
E797413
|
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: Varėna | Statement: [Dzūkija, includesCity, Varėna]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Varėna Context triple: [Dzūkija, includesCity, Varėna]
-
A.
Varėna
chosen
Varėna is a town in southeastern Lithuania known as the birthplace of the renowned composer and painter Mikalojus Konstantinas Čiurlionis.
-
B.
Varykino
Varykino is the remote country estate in Boris Pasternak's novel "Doctor Zhivago" where key emotional and dramatic events in Yuri Zhivago's life unfold.
-
C.
Varel
Varel is a coastal town in northwestern Germany known for its location near the Jade Bight and its mix of maritime industry and tourism.
-
D.
Vána
Vána is a lesser Vala in J.R.R. Tolkien’s legendarium, associated with eternal youth, blossoming flowers, and the ever-renewing vitality of nature.
-
E.
Vardenik
Vardenik is a mountain located in southeastern Serbia, known for its high peaks and scenic landscapes within the Balkan mountain system.
- 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_6a00c7aa83bc8190832d2f3903ce0081 |
completed | May 10, 2026, 6 p.m. |
Created at: April 10, 2026, 5:29 a.m.