Triple
T9005061
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fraueninsel |
E215121
|
entity |
| Predicate | tourismRegion |
P3030
|
FINISHED |
| Object | Chiemgau |
E207237
|
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: Chiemgau | Statement: [Fraueninsel, tourismRegion, Chiemgau]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Chiemgau Context triple: [Fraueninsel, tourismRegion, Chiemgau]
-
A.
Chiemgau region
chosen
The Chiemgau region is a picturesque area in southeastern Bavaria, Germany, known for its lakes, rolling Alpine foothills, and popular outdoor recreation opportunities.
-
B.
Andechs
Andechs is a Bavarian town best known for its historic Benedictine abbey and renowned monastic brewery that attract pilgrims and beer enthusiasts alike.
-
C.
Ostallgäu
Ostallgäu is a rural district in the Bavarian Alps of southern Germany, known for its picturesque landscapes and historic castles.
-
D.
Unterallgäu
Unterallgäu is a rural district in the Bavarian region of Swabia in southern Germany, known for its agricultural landscape and small towns.
-
E.
Flachgau
Flachgau is a district in the Austrian state of Salzburg, known for its picturesque Alpine landscapes and proximity to the city of Salzburg.
- 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_69ca83a12d648190b1e4fe11e8a31890 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc695afa34819086cf6fcce2997b5f |
completed | April 1, 2026, 12:39 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d05be6550081908d42bbae3c00cae3 |
completed | April 4, 2026, 12:31 a.m. |
Created at: March 30, 2026, 7:05 p.m.