Triple
T16824051
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Köthen |
E408967
|
entity |
| Predicate | hasTwinTown |
P919
|
FINISHED |
| Object | Siemianowice Śląskie |
—
|
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: Siemianowice Śląskie | Statement: [Köthen, hasTwinTown, Siemianowice Śląskie]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Siemianowice Śląskie Context triple: [Köthen, hasTwinTown, Siemianowice Śląskie]
-
A.
Siemianowice Śląskie
chosen
Siemianowice Śląskie is an industrial city in southern Poland, historically part of Upper Silesia and closely linked to the Katowice urban area.
-
B.
Skierniewice
Skierniewice is a historic city in central Poland known for its horticultural research center and annual Skierniewice Fruit and Vegetable Festival.
-
C.
Siemiatycze
Siemiatycze is a small town in northeastern Poland known for its multicultural heritage and location near the Bug River.
-
D.
Wodzisław Śląski
Wodzisław Śląski is a town in southern Poland known for its historic urban core and location in the industrial and mining region of Upper Silesia.
-
E.
Gorzów Śląski
Gorzów Śląski is a small town in southwestern Poland known for its location in the historical region of Upper Silesia.
- 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_69d88394566c8190b3dcbdc72935f7fa |
completed | April 10, 2026, 4:59 a.m. |
| NER | Named-entity recognition | batch_69e3b310ffec81908087e5aaacc4a7c2 |
completed | April 18, 2026, 4:36 p.m. |
Created at: April 10, 2026, 5:23 a.m.