Triple
T6588478
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Luton Airport Parkway |
E159287
|
entity |
| Predicate | hasAirportLinkType |
P23780
|
FINISHED |
| Object | automated people mover |
—
|
LITERAL 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: automated people mover | Statement: [Luton Airport Parkway, hasAirportLinkType, automated people mover]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAirportLinkType Context triple: [Luton Airport Parkway, hasAirportLinkType, automated people mover]
-
A.
associatedWithAirportType
Indicates that an entity has a connection or linkage to a specific category or type of airport.
-
B.
hasAirportCodeType
Indicates that an airport code is associated with a specific classification or type (e.g., IATA, ICAO, FAA).
-
C.
hasAirportRelatedFunction
Indicates that something performs a role, service, or activity specifically related to the operation, support, or functioning of an airport.
-
D.
belongsToAirport
Indicates that one entity is part of, associated with, or under the jurisdiction of a specific airport.
-
E.
connectsWithAirport
chosen
Indicates that there is a direct transportation or operational link established between an entity and an airport.
- F. None of above.
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_69c688366ce8819083f8883983c0df92 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6c07cdf048190945ca5810fb1de88 |
completed | March 27, 2026, 5:38 p.m. |
| PD | Predicate disambiguation | batch_69c6acfb462481909cb7aff5af4bca9d |
completed | March 27, 2026, 4:14 p.m. |
Created at: March 27, 2026, 1:55 p.m.