Triple
T12640639
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Grodno Region |
E301887
|
entity |
| Predicate | hasHistoricCity |
P3786
|
FINISHED |
| Object | Lida |
E290232
|
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: Lida | Statement: [Grodno Region, hasHistoricCity, Lida]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lida Context triple: [Grodno Region, hasHistoricCity, Lida]
-
A.
Lida
chosen
Lida is a historic city in present-day western Belarus, known for its medieval castle and former role as a regional center in the Grand Duchy of Lithuania.
-
B.
Lidan
Lidan is a river in southwestern Sweden that flows through the historical province of Västergötland before emptying into Lake Vänern.
-
C.
Luga
Luga is a small historic town in northwestern Russia known for its strategic location and role in regional transport and industry.
-
D.
Livny
Livny is a historic town in western Russia known as one of the principal urban centers of Oryol Oblast.
-
E.
Tarusa
Tarusa is a small historic town in western Russia known for its scenic location on the Oka River and its associations with Russian artists and writers.
- 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_69d7bdec9f9c8190b4bac675b7588211 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d9614ae6ac8190b42acbf2b0331fda |
completed | April 10, 2026, 8:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f668754acc8190b5585dbd35387867 |
completed | May 2, 2026, 9:11 p.m. |
Created at: April 9, 2026, 5:17 p.m.