Triple
T18470889
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Hard Interchange bus station |
E451295
|
entity |
| Predicate | servesOperator |
P5884
|
FINISHED |
| Object | National Express |
—
|
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: National Express | Statement: [The Hard Interchange bus station, servesOperator, National Express]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: National Express Context triple: [The Hard Interchange bus station, servesOperator, National Express]
-
A.
National Express
chosen
National Express is a major UK-based coach and bus operator providing long-distance and local passenger transport services domestically and internationally.
-
B.
TNT Express
TNT Express is an international courier and logistics company known for its global parcel delivery and express mail services.
-
C.
MTS Express
MTS Express is a faster, limited-stop bus service operated as part of the MTS Bus public transit system.
-
D.
Channel Express
Channel Express was a British airline that operated cargo and passenger services before rebranding and evolving into the low-cost carrier Jet2.com.
-
E.
United Express
United Express is the regional brand for United Airlines, operating shorter-haul feeder flights to connect passengers to United’s mainline network.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8d38465a0819099b9b42d2a662ac1 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e5305f428c81909980bd30d150e7dd |
completed | April 19, 2026, 7:43 p.m. |
Created at: April 10, 2026, 11:34 a.m.