Triple
T35936982
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Grindelwald |
E1039331
|
entity |
| Predicate | hasLakeViewAccess |
P9193
|
FINISHED |
| Object | Bachalpsee (via hiking trails) |
—
|
LITERAL 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: Bachalpsee (via hiking trails) | Statement: [Grindelwald, hasLakeViewAccess, Bachalpsee (via hiking trails)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLakeViewAccess Context triple: [Grindelwald, hasLakeViewAccess, Bachalpsee (via hiking trails)]
-
A.
hasWaterfrontView
Indicates that a property or location offers a direct view of a body of water from its premises.
-
B.
hasLakeLandscape
Indicates that an entity features or is characterized by a landscape that includes a lake.
-
C.
hasScenicViewOf
chosen
Indicates that one entity offers a visually appealing or picturesque view of another entity.
-
D.
hasScenicAccessTo
Indicates that one place or object provides a visually appealing or notable view of another place or object.
-
E.
hasLagoon
Indicates that one entity possesses, contains, or is characterized by a lagoon in relation to another entity or location.
- F. None of above.
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_69f76e24bbd0819096b837d35371639a |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69ff9e91bba08190af04b31ad815b13a |
completed | May 9, 2026, 8:52 p.m. |
| PD | Predicate disambiguation | batch_69ff9e00e4808190bde8f07e6519a72c |
completed | May 9, 2026, 8:50 p.m. |
Created at: May 3, 2026, 4:07 p.m.