Triple
T15053367
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oberhausen |
E379422
|
entity |
| Predicate | hasTwinTown |
P919
|
FINISHED |
| Object | Zabrze |
—
|
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: Zabrze | Statement: [Oberhausen, hasTwinTown, Zabrze]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Zabrze Context triple: [Oberhausen, hasTwinTown, Zabrze]
-
A.
Zabrze
chosen
Zabrze is an industrial city in the Silesian region of southern Poland, historically known for coal mining and heavy industry.
-
B.
Kluczbork
Kluczbork is a town in southern Poland known as a local administrative, cultural, and economic center in the Opole region.
-
C.
Kalisz
Kalisz is one of Poland’s oldest cities, located in the Greater Poland region and known for its historical architecture and cultural heritage.
-
D.
Zbrzyca
Zbrzyca is a river in northern Poland that flows through the Pomeranian region before joining the Brda River.
-
E.
Zawiercie
Zawiercie is a town in southern Poland’s Silesian Voivodeship, known historically as an industrial and railway hub near the Kraków-Częstochowa Upland.
- 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_69d85cd64d108190853797a95c11cc45 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69deda92091c81909180f486edf01405 |
completed | April 15, 2026, 12:23 a.m. |
Created at: April 10, 2026, 3:01 a.m.