Triple
T217768
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ryanair |
E4144
|
entity |
| Predicate | hubAirport |
P8171
|
FINISHED |
| Object | Manchester Airport |
E906
|
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: Manchester Airport | Statement: [Ryanair, hubAirport, Manchester Airport]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Manchester Airport Context triple: [Ryanair, hubAirport, Manchester Airport]
-
A.
Manchester Airport
chosen
Manchester Airport is a major international airport in North West England serving the Greater Manchester region and acting as a key hub for domestic and global 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.
Southend Airport
Southend Airport is a regional international airport in Essex, England, serving the London area with passenger and cargo flights.
-
D.
Gatwick Airport
Gatwick Airport is a major international airport serving the London area and is one of the busiest airports in the United Kingdom.
-
E.
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.
- 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_69a2573508588190b522c2476d91acfe |
completed | Feb. 28, 2026, 2:47 a.m. |
| NER | Named-entity recognition | batch_69a260c3037c8190ba7ddf328f249b74 |
completed | Feb. 28, 2026, 3:28 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a35878158c81908fba5b3cb4bfd054 |
completed | Feb. 28, 2026, 9:04 p.m. |
Created at: Feb. 28, 2026, 2:53 a.m.