Triple
T19823876
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mayrhofen |
E476266
|
entity |
| Predicate | hasNearbyValley |
P350
|
FINISHED |
| Object | Tuxertal |
—
|
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: Tuxertal | Statement: [Mayrhofen, hasNearbyValley, Tuxertal]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tuxertal Context triple: [Mayrhofen, hasNearbyValley, Tuxertal]
-
A.
Tuxertal
chosen
Tuxertal is a scenic alpine valley in the Austrian Tyrol, known for its year-round skiing and access to the Hintertux Glacier.
-
B.
Klostertal
Klostertal is a scenic alpine valley in the Austrian state of Vorarlberg, known for its mountain landscapes, ski areas, and access to the Arlberg region.
-
C.
Kammeltal
Kammeltal is a municipality in the Bavarian region of Swabia in southern Germany.
-
D.
Löstertal
Löstertal is a locality within the town of Wadern in the Saarland region of Germany, known for its rural character and scenic surroundings.
-
E.
Stanzertal
Stanzertal is an alpine valley in the Austrian state of Tyrol, known for its scenic landscapes and proximity to major ski resorts such as St. Anton am Arlberg.
- 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_69d8e51c7c188190b926f3a2a7b5f881 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e6550070c4819099e1f057b9a8849e |
completed | April 20, 2026, 4:32 p.m. |
Created at: April 10, 2026, 1:50 p.m.