Triple
T12576950
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marienbrücke (Queen Mary’s Bridge) |
E300232
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Ostallgäu |
E215162
|
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: Ostallgäu | Statement: [Marienbrücke (Queen Mary’s Bridge), locatedIn, Ostallgäu]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ostallgäu Context triple: [Marienbrücke (Queen Mary’s Bridge), locatedIn, Ostallgäu]
-
A.
Ostallgäu
chosen
Ostallgäu is a rural district in the Bavarian Alps of southern Germany, known for its picturesque landscapes and historic castles.
-
B.
Flachgau
Flachgau is a district in the Austrian state of Salzburg, known for its picturesque Alpine landscapes and proximity to the city of Salzburg.
-
C.
Weidach
Weidach is a locality or district that forms part of the municipality of Blaustein in the state of Baden-Württemberg, Germany.
-
D.
Gosau
Gosau is a picturesque alpine village in Austria’s Salzkammergut region, known for its dramatic mountain scenery, traditional rural character, and proximity to the Dachstein massif.
-
E.
Unterallgäu
Unterallgäu is a rural district in the Bavarian region of Swabia in southern Germany, known for its agricultural landscape and small towns.
- 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_69d7bde87b648190bcd0266e9efde098 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d954a73c148190bba8f16b1232fd46 |
completed | April 10, 2026, 7:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f67190a20c8190918b465b67d25869 |
completed | May 2, 2026, 9:50 p.m. |
Created at: April 9, 2026, 4:51 p.m.