Triple
T19391634
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brenz |
E485081
|
entity |
| Predicate | flowsThrough |
P225
|
FINISHED |
| Object | Lauingen |
—
|
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: Lauingen | Statement: [Brenz, flowsThrough, Lauingen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lauingen Context triple: [Brenz, flowsThrough, Lauingen]
-
A.
Lauingen
chosen
Lauingen is a historic Bavarian town in southern Germany, best known as the birthplace of the medieval scholar and philosopher Albert the Great.
-
B.
Herzogenaurach
Herzogenaurach is a Bavarian town in Germany best known as the birthplace and headquarters of the global sportswear brands Adidas and Puma.
-
C.
Gröbenzell
Gröbenzell is a suburban town in Upper Bavaria, Germany, known for its residential character and proximity to Munich.
-
D.
Lauchheim
Lauchheim is a small town in the eastern part of Baden-Württemberg, Germany, known for its historic center and location along the Jagst River.
-
E.
Schönteichen
Schönteichen is a small municipality in the Free State of Saxony in eastern Germany.
- 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_69d8e8d460d88190abf0591c5c9d2b0c |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e61b45caec81909dafdf66b361effd |
completed | April 20, 2026, 12:25 p.m. |
Created at: April 10, 2026, 1:36 p.m.