Triple
T20667820
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Freising district |
E507938
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Hallbergmoos |
—
|
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: Hallbergmoos | Statement: [Freising district, contains, Hallbergmoos]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hallbergmoos Context triple: [Freising district, contains, Hallbergmoos]
-
A.
Hallbergmoos
chosen
Hallbergmoos is a municipality in Bavaria, Germany, known for hosting major aerospace and technology companies near Munich.
-
B.
Haigerloch
Haigerloch is a small historic town in the Zollernalb district of Baden-Württemberg, Germany, known for its picturesque old town and former role in Germany’s World War II nuclear research.
-
C.
Sulzemoos
Sulzemoos is a small municipality in Bavaria, Germany, located northwest of Munich in the district of Dachau.
-
D.
Röhrmoos
Röhrmoos is a municipality in Upper Bavaria, Germany, situated within the district of Dachau.
-
E.
Hasliberg
Hasliberg is a Swiss alpine village and municipality in the canton of Bern, known for its mountain scenery and ski and hiking resort facilities.
- 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_69e0b4c059bc81908ea762cd73ea4424 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6b5c4c4608190ae17da4a59e5ae80 |
completed | April 20, 2026, 11:24 p.m. |
Created at: April 16, 2026, 11:44 a.m.