Triple
T14197231
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nuneaton railway station |
E351867
|
entity |
| Predicate | hasServiceTo |
P6787
|
FINISHED |
| Object | Stansted Airport |
E15363
|
NE 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: Stansted Airport | Statement: [Nuneaton railway station, hasServiceTo, Stansted Airport]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Stansted Airport Context triple: [Nuneaton railway station, hasServiceTo, Stansted Airport]
-
A.
Stansted Airport
chosen
Stansted Airport is a major international airport serving the London area, particularly known as a hub for low-cost and European short-haul flights.
-
B.
Luton Airport
Luton Airport is a major international airport north of London that serves as a key hub for low-cost airlines and short-haul European flights.
-
C.
Gatwick Airport
Gatwick Airport is a major international airport serving the London area and is one of the busiest airports in the United Kingdom.
-
D.
Heathrow Airport
Heathrow Airport is the United Kingdom’s largest and busiest international airport, serving as a major global aviation hub for London.
-
E.
Southend Airport
Southend Airport is a regional international airport in Essex, England, serving the London area with passenger and cargo flights.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d827894ac0819097803e57f3227b23 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de61e30f208190b61c1c7bd3501156 |
completed | April 14, 2026, 3:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd324b86748190b3e0a39383969cc7 |
completed | May 8, 2026, 12:46 a.m. |
Created at: April 10, 2026, 1:04 a.m.