Triple
T13900226
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dingolfing |
E334197
|
entity |
| Predicate | locatedOnRiver |
P165
|
FINISHED |
| Object | Isar |
E66587
|
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: Isar | Statement: [Dingolfing, locatedOnRiver, Isar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Isar Context triple: [Dingolfing, locatedOnRiver, Isar]
-
A.
Isar
chosen
The Isar is a major river in the Austrian and German Alps that flows through cities such as Munich before joining the Danube.
-
B.
Isar
Isar is a structured, human-readable proof language designed for writing formal proofs within the Isabelle interactive theorem prover.
-
C.
Isar valley
The Isar valley is a scenic river valley in Bavaria, Germany, known for its picturesque landscapes, forests, and traditional towns along the Isar River.
-
D.
Aichach
Aichach is a town in Bavaria, Germany, known in part for its prison where several Nazi war criminals, including Ilse Koch, were held and died.
-
E.
Hadern
Hadern is a borough in the southwest of Munich, Germany, known for its residential character and the large Waldfriedhof cemetery.
- 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_69d81c5eaa9c819083b1ff8689179565 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de25d8897881908b770cdb565898d4 |
completed | April 14, 2026, 11:32 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd27f8f388819096c7c33b90f9ac4c |
completed | May 8, 2026, 12:02 a.m. |
Created at: April 9, 2026, 10:15 p.m.