Triple
T46278
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Manchester Airport |
E906
|
entity |
| Predicate | isBaseFor |
P2421
|
FINISHED |
| Object |
TUI Airways
TUI Airways is a British charter and scheduled airline that primarily serves leisure destinations across Europe and worldwide as part of the TUI Group.
|
E16522
|
NE FINISHED |
How this triple was built (4 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: TUI Airways | Statement: [Manchester Airport, isBaseFor, TUI Airways]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: TUI Airways Context triple: [Manchester Airport, isBaseFor, TUI Airways]
-
A.
Ryanair
Ryanair is a major Irish low-cost airline known for its extensive network of short-haul flights across Europe.
-
B.
easyJet
easyJet is a major British low-cost airline operating extensive domestic and European routes.
-
C.
Manchester Airports Group
Manchester Airports Group is a leading UK-based airport operator that owns and manages several major airports, including Manchester, London Stansted, and East Midlands.
-
D.
Qatar Airways
Qatar Airways is the state-owned flag carrier of Qatar, renowned for its extensive global network and high-end service standards.
-
E.
Jet2.com
Jet2.com is a British low-cost leisure airline that operates scheduled and charter flights across Europe from multiple UK bases.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: TUI Airways Triple: [Manchester Airport, isBaseFor, TUI Airways]
Generated description
TUI Airways is a British charter and scheduled airline that primarily serves leisure destinations across Europe and worldwide as part of the TUI Group.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: TUI Airways Target entity description: TUI Airways is a British charter and scheduled airline that primarily serves leisure destinations across Europe and worldwide as part of the TUI Group.
-
A.
Ryanair
Ryanair is a major Irish low-cost airline known for its extensive network of short-haul flights across Europe.
-
B.
easyJet
easyJet is a major British low-cost airline operating extensive domestic and European routes.
-
C.
Manchester Airports Group
Manchester Airports Group is a leading UK-based airport operator that owns and manages several major airports, including Manchester, London Stansted, and East Midlands.
-
D.
Qatar Airways
Qatar Airways is the state-owned flag carrier of Qatar, renowned for its extensive global network and high-end service standards.
-
E.
Jet2.com
Jet2.com is a British low-cost leisure airline that operates scheduled and charter flights across Europe from multiple UK bases.
- F. None of above. chosen
Provenance (5 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_69a2480baefc81909951b14058479aa2 |
completed | Feb. 28, 2026, 1:42 a.m. |
| NER | Named-entity recognition | batch_69a24ec333fc8190b66776b947e0bdbd |
completed | Feb. 28, 2026, 2:11 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a2b85b11c08190b97de9b0382be6d5 |
completed | Feb. 28, 2026, 9:41 a.m. |
| NEDg | Description generation | batch_69a2b8ee35048190b096296a42481b9c |
completed | Feb. 28, 2026, 9:44 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69a2b99440e88190ab7c8525609569f1 |
completed | Feb. 28, 2026, 9:47 a.m. |
Created at: Feb. 28, 2026, 1:47 a.m.