Triple
T21896125
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Celle |
E540682
|
entity |
| Predicate | hasTwinTown |
P919
|
FINISHED |
| Object | Sumy |
—
|
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: Sumy | Statement: [Celle, hasTwinTown, Sumy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sumy Context triple: [Celle, hasTwinTown, Sumy]
-
A.
Sumy
chosen
Sumy is a regional city in northeastern Ukraine known as the administrative center of Sumy Oblast and an important cultural, educational, and industrial hub.
-
B.
Rivne
Rivne is a city in western Ukraine that serves as an important regional administrative, economic, and cultural center.
-
C.
Ternopil
Ternopil is a city in western Ukraine known as a regional cultural and economic center with a historic old town and a picturesque lakeside setting.
-
D.
Uzhhorod
Uzhhorod is a historic city in western Ukraine near the Slovak and Hungarian borders, known for its multicultural heritage and as the administrative center of Zakarpattia Oblast.
-
E.
Khmelnytskyi
Khmelnytskyi is a regional city in western Ukraine known as an important administrative, economic, and cultural center.
- 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_69e0c47a95908190ae3e19b716accb3d |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f11fc700c08190a470fe1ad76c8509 |
completed | April 28, 2026, 8:59 p.m. |
Created at: April 16, 2026, 7:07 p.m.