Triple
T2148956
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Leeds railway station |
E47134
|
entity |
| Predicate | hasNearbyTramOrLightRail |
P29999
|
FINISHED |
| Object | Leeds city centre bus rapid transit stops |
—
|
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: Leeds city centre bus rapid transit stops | Statement: [Leeds railway station, hasNearbyTramOrLightRail, Leeds city centre bus rapid transit stops]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNearbyTramOrLightRail Context triple: [Leeds railway station, hasNearbyTramOrLightRail, Leeds city centre bus rapid transit stops]
-
A.
hasNearbyTramStop
chosen
Indicates that a location has a tram stop situated within a short walking distance or close proximity.
-
B.
hasNearbyRailway
Indicates that one entity is located close to a railway associated with or relevant to another entity.
-
C.
hasTramway
Indicates that a location or area is served by, contains, or is connected to a tramway system.
-
D.
hasPublicTransportStop
Indicates that a location or area contains or is served by a public transport stop, such as a bus, tram, or train stop.
-
E.
hasNearbyRailwayStation
Indicates that a railway station is located within a short or convenient distance from the referenced entity.
- 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_69a88a1933e0819094f18426ed74180f |
completed | March 4, 2026, 7:38 p.m. |
| NER | Named-entity recognition | batch_69abbeaa14bc81908486683decd7ae42 |
completed | March 7, 2026, 5:59 a.m. |
| PD | Predicate disambiguation | batch_69abbd9846e88190b6c2941dd9ce7749 |
completed | March 7, 2026, 5:54 a.m. |
Created at: March 4, 2026, 7:44 p.m.