Triple
T11462850
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vilna |
E271703
|
entity |
| Predicate | hasDemonym |
P191
|
FINISHED |
| Object | Vilnian |
E271703
|
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: Vilnian | Statement: [Vilna, hasDemonym, Vilnian]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Vilnian Context triple: [Vilna, hasDemonym, Vilnian]
-
A.
Vilna
chosen
Vilna is the historical name for Vilnius, the capital city of Lithuania and a major cultural and political center of the region.
-
B.
Mitau
Mitau, historically known as the capital of the Duchy of Courland and Semigallia, is the former German name for the city now called Jelgava in present-day Latvia.
-
C.
Baltiysk
Baltiysk is a Russian port town in the Kaliningrad Oblast, strategically located on the Baltic Sea and serving as an important naval base.
-
D.
Litvak
Litvak is a surname most notably borne by Anatole Litvak, a Ukrainian-born film director who worked extensively in Hollywood and Europe.
-
E.
Kovno
Kovno is the historical name for Kaunas, a major city in Lithuania that was once part of the Russian Empire and had a significant Jewish community.
- 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_69d6aae0c8d881908a5a360c0be3242e |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d822f488248190b9f603cd31c72174 |
completed | April 9, 2026, 10:06 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e5e92a7c2881908d85009a6069b2e4 |
completed | April 20, 2026, 8:51 a.m. |
Created at: April 8, 2026, 9:35 p.m.