Triple
T17755190
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marijampolė |
E443213
|
entity |
| Predicate | twinnedWith |
P1072
|
FINISHED |
| Object | Kobryn |
E1266008
|
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: Kobryn | Statement: [Marijampolė, twinnedWith, Kobryn]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kobryn Context triple: [Marijampolė, twinnedWith, Kobryn]
-
A.
Kobryn
chosen
Kobryn is a historic town in southwestern Belarus known for its location at the confluence of the Mukhavets and Dnieper–Bug Canal and its role as a regional cultural and economic center.
-
B.
Kamenets-Podolsk
Kamenets-Podolsk is a historic city in western Ukraine that became the site of one of the earliest and largest mass shootings of Jews during the Holocaust.
-
C.
Volochysk
Volochysk is a town in western Ukraine known as a local administrative and transportation center near the border with Ternopil Oblast.
-
D.
Babruysk
Babruysk is a historic city in eastern Belarus known as a former major Jewish cultural center and regional industrial hub.
-
E.
Dzyarzhynsk
Dzyarzhynsk is a town in Belarus known for its proximity to Dzyarzhynskaya Hara, the country’s highest point.
- 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_69d8b9edf16c8190a59ebd245d378f4f |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e4841e7050819083a4e638ca7484f7 |
completed | April 19, 2026, 7:28 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0306e7b47c8190842dfc27d2f90b78 |
completed | May 12, 2026, 10:54 a.m. |
Created at: April 10, 2026, 10:10 a.m.