Triple
T15438026
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Meschede |
E369819
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | Bestwig |
E564062
|
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: Bestwig | Statement: [Meschede, locatedNear, Bestwig]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bestwig Context triple: [Meschede, locatedNear, Bestwig]
-
A.
Bestwig
chosen
Bestwig is a municipality in the Hochsauerland district of North Rhine-Westphalia, Germany, known for its location in the Sauerland region and its scenic, hilly landscape.
-
B.
Weigert
Weigert is a German-language surname borne by various notable individuals in fields such as science, sports, and the arts.
-
C.
Stahlecker
Stahlecker is a German-language surname most notably associated with Franz Walter Stahlecker, a high-ranking SS officer and Nazi official during World War II.
-
D.
Weinert
Weinert is a German-language surname borne by various notable individuals in fields such as the arts, sciences, and public life.
-
E.
Lehwaldt
Lehwaldt was a Prussian field marshal best known for commanding Prussian forces in the early campaigns of the Seven Years' War in Europe.
- 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_69d85a19180081909925012fbf4e62a3 |
completed | April 10, 2026, 2:02 a.m. |
| NER | Named-entity recognition | batch_69e03edca064819081510bf303271062 |
completed | April 16, 2026, 1:43 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff21a7d44481909a26b5cc331a3259 |
completed | May 9, 2026, 11:59 a.m. |
Created at: April 10, 2026, 3:21 a.m.