Triple
T21035870
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lewin Kłodzki |
E518187
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Sudetes |
—
|
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: Sudetes | Statement: [Lewin Kłodzki, locatedIn, Sudetes]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sudetes Context triple: [Lewin Kłodzki, locatedIn, Sudetes]
-
A.
Sudetes
chosen
The Sudetes are a mountain range in Central Europe spanning parts of Poland, the Czech Republic, and Germany, known for their forested peaks, mineral resources, and popular spa and ski resorts.
-
B.
Nausėda
Nausėda is a Lithuanian surname most prominently associated with Gitanas Nausėda, the President of Lithuania.
-
C.
Balta
Balta is a city that gained historical significance as a strategic location captured during the Uman–Botoșani offensive in World War II.
-
D.
Aukštaitija
Aukštaitija is a historical and ethnographic region in northeastern Lithuania known for its lakes, forests, and strong preservation of traditional Lithuanian culture and dialects.
-
E.
Vianen
Vianen is a historic Dutch town known for its medieval city center and location near major rivers in the western Netherlands.
- 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_69e0b503275c8190afd9a163f997c709 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e6fc865ca88190abf336ee9012fa77 |
completed | April 21, 2026, 4:26 a.m. |
Created at: April 16, 2026, 2:02 p.m.