Triple
T18126225
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zurich Wiedikon |
E433881
|
entity |
| Predicate | hasGoodPublicTransportConnections |
P130540
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Zurich Wiedikon, hasGoodPublicTransportConnections, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGoodPublicTransportConnections Context triple: [Zurich Wiedikon, hasGoodPublicTransportConnections, true]
-
A.
hasPublicTransportConnection
Indicates that there is an available public transportation link or service connecting the related entities.
-
B.
hasPublicTransitInfrastructure
Indicates that a location or area is equipped with facilities and systems that support public transportation services (e.g., buses, trains, trams).
-
C.
hasPublicTransitProvider
Indicates that a place or region is served by a specific public transit operating organization or agency.
-
D.
hasPublicTransitFunction
Indicates that something serves a role or provides a service related to public transportation operations or infrastructure.
-
E.
hasPublicTransitMode
Indicates that a location, route, or service is associated with or supports a specific mode of public transportation (e.g., bus, train, tram).
- 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_69d8b909e8cc81908df4cc2b8ea6d11f |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4ddee1efc8190b04324b98de5c9d0 |
completed | April 19, 2026, 1:51 p.m. |
| PD | Predicate disambiguation | batch_69e43313ca788190baa224269e71de49 |
completed | April 19, 2026, 1:42 a.m. |
| PDg | Predicate description generation | batch_69e438f5ae2c8190b11dee46534fa5a9 |
completed | April 19, 2026, 2:07 a.m. |
Created at: April 10, 2026, 10:29 a.m.