Triple
T10445687
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Linköping Central Station |
E246279
|
entity |
| Predicate | hasPublicTransportInterchange |
P2423
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Linköping Central Station, hasPublicTransportInterchange, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPublicTransportInterchange Context triple: [Linköping Central Station, hasPublicTransportInterchange, yes]
-
A.
hasBusInterchange
chosen
Indicates that one transport-related entity includes, contains, or is associated with a bus interchange facility.
-
B.
hasPublicTransportConnection
Indicates that there is an available public transportation link or service connecting the related entities.
-
C.
hasPublicTransportStop
Indicates that a location or area contains or is served by a public transport stop, such as a bus, tram, or train stop.
-
D.
isPublicTransportStation
Indicates that a location functions as a station or stop used by public transportation services such as buses, trains, trams, or subways.
-
E.
hasPublicTransitRole
Indicates that an entity holds a specific functional role or responsibility within a public transit system.
- 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_69d381c04fe08190957c26c526a3b05a |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4fe083cd881909d2d8ad75d1d94cb |
completed | April 7, 2026, 12:52 p.m. |
| PD | Predicate disambiguation | batch_69d4fb73a5e48190a8df4775bc5da80f |
completed | April 7, 2026, 12:41 p.m. |
Created at: April 6, 2026, 12:16 p.m.