Triple
T21305284
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mur River |
E525180
|
entity |
| Predicate | sourceLocation |
P40
|
FINISHED |
| Object | Lungau |
E470003
|
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: Lungau | Statement: [Mur River, sourceLocation, Lungau]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lungau Context triple: [Mur River, sourceLocation, Lungau]
-
A.
Lungau
chosen
Lungau is a mountainous region in the southeastern part of the Austrian state of Salzburg, known for its alpine landscapes, traditional villages, and outdoor recreation.
-
B.
Lungren
Lungren is a surname most notably associated with Dan Lungren, an American politician who served as California’s attorney general and a U.S. congressman.
-
C.
Lungin
Lungin is a Russian surname most notably associated with film director and screenwriter Pavel Lungin.
-
D.
Lanin
Lanín is a prominent stratovolcano in the Andes on the border between Argentina and Chile, known for its conical snow-capped peak and popularity among climbers.
-
E.
Luhanka
Luhanka is a small rural municipality in central Finland known for its lakeside landscapes and tranquil countryside.
- 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_69e0b518b8948190ad69cf9a8784d397 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e75aa3f90481909b212bdbf00c2bb0 |
completed | April 21, 2026, 11:08 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a099ed32130819081479d9845d74ac3 |
completed | May 17, 2026, 10:56 a.m. |
Created at: April 16, 2026, 4:05 p.m.