Triple
T2123807
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Châteauroux |
E43984
|
entity |
| Predicate | twinTown |
P1072
|
FINISHED |
| Object | Olsztyn |
E372338
|
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: Olsztyn | Statement: [Châteauroux, twinTown, Olsztyn]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Olsztyn Context triple: [Châteauroux, twinTown, Olsztyn]
-
A.
Olsztyn
chosen
Olsztyn is a historic city in northern Poland known for its medieval architecture, lakes, and role as the capital of the Warmian-Masurian Voivodeship.
-
B.
Ostróda
Ostróda is a town in northern Poland known for its lakeside setting, tourism, and role as a local economic and cultural center.
-
C.
Bydgoszcz
Bydgoszcz is a major city in northern Poland known as an important economic, cultural, and academic center on the Brda and Vistula rivers.
-
D.
Koszalin
Koszalin is a city in northwestern Poland near the Baltic Sea, known as a regional cultural and economic center.
-
E.
Olsztynek
Olsztynek is a small historic town in northern Poland known for its open-air ethnographic museum and location within the picturesque Warmian-Masurian lake district.
- 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_69a88717cfe48190b7ecdd68c824848a |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abbb55cb2c8190aab8199da3335032 |
completed | March 7, 2026, 5:44 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b503cf9f8881908dc371d5acb952cf |
completed | March 14, 2026, 6:44 a.m. |
Created at: March 4, 2026, 7:44 p.m.