Triple
T9472397
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Langscheid |
E228423
|
entity |
| Predicate | partOf |
P40
|
FINISHED |
| Object | Sundern |
E228422
|
NE FINISHED |
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: Sundern | Statement: [Langscheid, partOf, Sundern]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sundern Context triple: [Langscheid, partOf, Sundern]
-
A.
Sundern
chosen
Sundern is a town in the Hochsauerland district of North Rhine-Westphalia, Germany, known for its proximity to the Sorpe Dam and the surrounding Sauerland recreational region.
-
B.
Winsum
Winsum is a historic village and former municipality in the Dutch province of Groningen, known for its old churches, windmills, and picturesque canals.
-
C.
Nottuln
Nottuln is a historic municipality in North Rhine-Westphalia, Germany, known for its medieval architecture and role in regional conflicts.
-
D.
Teesdorf
Teesdorf is a municipality in Lower Austria known for its motorsport testing facilities and rural setting south of Vienna.
-
E.
Starnberg
Starnberg is a lakeside town in Bavaria, Germany, known for its affluent residential character and scenic location on Lake Starnberg southwest of Munich.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69ca847162c48190b079076c9595513c |
completed | March 30, 2026, 2:10 p.m. |
| NER | Named-entity recognition | batch_69cd7fef6f288190b2d158c829b31de9 |
completed | April 1, 2026, 8:28 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d122d625fc8190b8222930449ad3da |
completed | April 4, 2026, 2:40 p.m. |
Created at: March 30, 2026, 7:54 p.m.