Triple
T17658182
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Glitterheim–Spiterstulen routes |
E440178
|
entity |
| Predicate | hasAccommodationAtEndpoints |
P128426
|
FINISHED |
| Object | mountain lodges |
—
|
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: mountain lodges | Statement: [Glitterheim–Spiterstulen routes, hasAccommodationAtEndpoints, mountain lodges]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAccommodationAtEndpoints Context triple: [Glitterheim–Spiterstulen routes, hasAccommodationAtEndpoints, mountain lodges]
-
A.
hasAccommodation
Indicates that an entity provides, owns, or is associated with a place for someone to stay or live.
-
B.
passengerAccommodation
Indicates that an entity provides or is designated as seating, lodging, or space intended for use by passengers.
-
C.
hasEndpointAirport
Indicates that something, such as a route or flight, has a specific airport as one of its terminal endpoints.
-
D.
hasEndpointCity
Indicates that a route, connection, or path terminates at a particular city as one of its endpoints.
-
E.
accommodationModel
Indicates the specific type or structure of lodging arrangement that characterizes how an accommodation is organized or provided.
- F. None of above. chosen
Provenance (4 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_69d8b9e87e18819087104a44dc4dc5b1 |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e46ea3b4cc81908eec7032cf221d49 |
completed | April 19, 2026, 5:56 a.m. |
| PD | Predicate disambiguation | batch_69e3cddc87188190ac2f049b86038676 |
completed | April 18, 2026, 6:30 p.m. |
| PDg | Predicate description generation | batch_69e3cfaac2b881909e1140339eb1a0dd |
completed | April 18, 2026, 6:38 p.m. |
Created at: April 10, 2026, 9:33 a.m.