Triple
T2400188
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vennbahn railway |
E47746
|
entity |
| Predicate | hasRouteFeature |
P37949
|
FINISHED |
| Object | passes through sparsely populated highland areas |
—
|
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: passes through sparsely populated highland areas | Statement: [Vennbahn railway, hasRouteFeature, passes through sparsely populated highland areas]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRouteFeature Context triple: [Vennbahn railway, hasRouteFeature, passes through sparsely populated highland areas]
-
A.
hasRoute
Indicates that there exists a path or connection enabling travel or communication from one entity to another.
-
B.
hasRouteType
Indicates that there is a specific kind or category of route associated with an entity (e.g., road, rail, bus line).
-
C.
hasRouteMaps
Indicates that one entity possesses or provides route maps that describe paths, directions, or connections related to another entity.
-
D.
hasRouteAlignment
Indicates that there is a defined spatial or geometric alignment associated with a route or pathway.
-
E.
hasRouteDirection
Indicates that a specified route is associated with a particular travel direction (e.g., inbound, outbound, northbound).
- 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_69a88a1c450c81909f61abb8b6863885 |
completed | March 4, 2026, 7:38 p.m. |
| NER | Named-entity recognition | batch_69abc8c95d8c819088e4bb4fb32452ae |
completed | March 7, 2026, 6:42 a.m. |
| PD | Predicate disambiguation | batch_69abc5a3825c81909ec6111dfc165453 |
completed | March 7, 2026, 6:28 a.m. |
| PDg | Predicate description generation | batch_69abc664317c8190a6bb5a5065c21bde |
completed | March 7, 2026, 6:32 a.m. |
Created at: March 4, 2026, 7:57 p.m.