Triple
T16561006
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kraichgau |
E402336
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Bruchsal |
—
|
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: Bruchsal | Statement: [Kraichgau, contains, Bruchsal]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bruchsal Context triple: [Kraichgau, contains, Bruchsal]
-
A.
Bruchsal
chosen
Bruchsal is a town in the state of Baden-Württemberg in southwestern Germany, known for its baroque palace and asparagus cultivation.
-
B.
Fritzlar
Fritzlar is a historic town in northern Hesse, Germany, known for its well-preserved medieval old town and its significance in early German Christian history.
-
C.
Badenweiler
Badenweiler is a spa town in southwestern Germany’s Black Forest region, known for its thermal baths and as the place where Russian writer Anton Chekhov died.
-
D.
Rastatt
Rastatt is a historic town in southwestern Germany, known for its Baroque architecture and its role as the site of significant early 18th-century peace negotiations.
-
E.
Wörth am Rhein
Wörth am Rhein is a town in the German state of Rhineland-Palatinate, situated on the Rhine River near Karlsruhe and known for its industrial facilities and transport links.
- 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_69d8838648088190acf97ef11fc3f61b |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e3576d88288190b33543bea4706a36 |
completed | April 18, 2026, 10:05 a.m. |
Created at: April 10, 2026, 5:15 a.m.