Triple
T17954928
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Тула |
E448919
|
entity |
| Predicate | hasTwinTown |
P919
|
FINISHED |
| Object | Бельцы |
—
|
NE NERFINISHED |
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: Бельцы | Statement: [Тула, hasTwinTown, Бельцы]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Бельцы Context triple: [Тула, hasTwinTown, Бельцы]
-
A.
Beltsy
chosen
Beltsy is an alternative name for Bălți, a major city in northern Moldova known as an important economic and cultural center.
-
B.
Berdiansk
Berdiansk is a port city on the northern coast of the Sea of Azov in southeastern Ukraine, known for its beaches and resort facilities.
-
C.
Zbarazh
Zbarazh is a historic town in western Ukraine known for its medieval castle and role in regional political and military history.
-
D.
Pryluky
Pryluky is a historic city in northern Ukraine known for its Cossack heritage and role as a regional cultural and economic center.
-
E.
Barysaw
Barysaw is a city in Belarus known as an important industrial and transportation center northeast of Minsk.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8b9f8cca8819099836916c56b7c95 |
completed | April 10, 2026, 8:51 a.m. |
| NER | Named-entity recognition | batch_69e4afaf1ddc8190b480147ac35a4912 |
completed | April 19, 2026, 10:34 a.m. |
Created at: April 10, 2026, 10:21 a.m.