Triple
T7302147
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Farringdon |
E167882
|
entity |
| Predicate | connectsTo |
P845
|
FINISHED |
| Object | Luton Airport |
E15779
|
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: Luton Airport | Statement: [Farringdon, connectsTo, Luton Airport]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Luton Airport Context triple: [Farringdon, connectsTo, Luton Airport]
-
A.
Luton Airport
chosen
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.
-
B.
Stansted Airport
Stansted Airport is a major international airport serving the London area, particularly known as a hub for low-cost and European short-haul flights.
-
C.
Southend Airport
Southend Airport is a regional international airport in Essex, England, serving the London area with passenger and cargo flights.
-
D.
Bristol Airport
Bristol Airport is a major regional airport in South West England serving domestic and international flights, notably as a key base for low-cost carriers like easyJet.
-
E.
Coventry Airport
Coventry Airport is a regional airport in the West Midlands of England that has historically handled charter, cargo, and general aviation 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_69c6888c820881909fc68f689fe1c251 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6ebb09164819099c4479d48c1688a |
completed | March 27, 2026, 8:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c8be10c5b081908210981ce9c45bd9 |
completed | March 29, 2026, 5:52 a.m. |
Created at: March 27, 2026, 3:01 p.m.