Triple
T12600542
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bundesstraße 7 |
E300845
|
entity |
| Predicate | passesThrough |
P225
|
FINISHED |
| Object | Brilon |
E573036
|
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: Brilon | Statement: [Bundesstraße 7, passesThrough, Brilon]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Brilon Context triple: [Bundesstraße 7, passesThrough, Brilon]
-
A.
Brilon
chosen
Brilon is a historic town in the Hochsauerland region of North Rhine-Westphalia, Germany, known for its medieval center and surrounding forested landscapes.
-
B.
Scharbeutz
Scharbeutz is a Baltic Sea resort town in northern Germany known for its long sandy beaches and seaside tourism.
-
C.
Bretten
Bretten is a historic town in the German state of Baden-Württemberg, known as the birthplace of the Protestant reformer Philip Melanchthon.
-
D.
Schongau
Schongau is a historic Bavarian town in southern Germany known for its well-preserved medieval old town and location along the Romantic Road.
-
E.
Freudenstadt
Freudenstadt is a spa and holiday town in southwestern Germany known for its large market square and location in the northern Black Forest.
- 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_69d7bdea2ca881908f379526c13b1145 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d954d1f6ac8190ab21ca7bcbc80129 |
completed | April 10, 2026, 7:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f65ec92c6c8190bd2d193e70940407 |
completed | May 2, 2026, 8:30 p.m. |
Created at: April 9, 2026, 5:09 p.m.