Triple
T9472449
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sorpesee |
E228424
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | Amecke |
E800254
|
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: Amecke | Statement: [Sorpesee, locatedNear, Amecke]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Amecke Context triple: [Sorpesee, locatedNear, Amecke]
-
A.
Amecke
chosen
Amecke is a village and district of the town of Sundern in the Hochsauerland region of North Rhine-Westphalia, Germany.
-
B.
Weyts
Weyts is a Dutch-language surname of Belgian origin, notably borne by Flemish politician Ben Weyts.
-
C.
Boesinghe
Boesinghe is a village in West Flanders, Belgium, known for its proximity to key World War I battlefields along the Yser Front.
-
D.
Kanegem
Kanegem is a small village in West Flanders, Belgium, known for its historic church and rural character.
-
E.
Michelbeke
Michelbeke is a village in the municipality of Brakel in East Flanders, Belgium, known for its rural character and cycling-friendly landscape.
- 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_69d12ce6c7c88190825bf618f1f1f9b5 |
completed | April 4, 2026, 3:23 p.m. |
Created at: March 30, 2026, 7:54 p.m.