Triple
T30192949
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hochfelln |
E767543
|
entity |
| Predicate | hasCableCarMiddleStationIn |
P85429
|
FINISHED |
| Object | Bergen (Chiemgau) |
—
|
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: Bergen (Chiemgau) | Statement: [Hochfelln, hasCableCarMiddleStationIn, Bergen (Chiemgau)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCableCarMiddleStationIn Context triple: [Hochfelln, hasCableCarMiddleStationIn, Bergen (Chiemgau)]
-
A.
hasCableCar
Indicates that one entity possesses, operates, or is served by a cable car system connecting it to other locations or points.
-
B.
cableCarStations
chosen
Indicates that there is a cable car connection or service operating between the referenced stations.
-
C.
hasCableCarLineNearby
Indicates that there is at least one cable car line located in close proximity to the referenced entity.
-
D.
hasMountainRailwayConnectionTo
Indicates that there is a railway line specifically adapted for mountainous terrain that connects one location to another.
-
E.
middleStation
Indicates that one station lies between two other stations along a route or line, serving as an intermediate point in the sequence.
- 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_69f2247db1108190835c0727c97637c3 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69fdbc5ef46c8190bbcfb9798f4615b7 |
completed | May 8, 2026, 10:35 a.m. |
| PD | Predicate disambiguation | batch_69fdbb270338819082ce3f73903e884f |
completed | May 8, 2026, 10:29 a.m. |
Created at: April 29, 2026, 7:29 p.m.