Triple
T1274372
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Luton Airport |
E15779
|
entity |
| Predicate | distanceFromLondonCentre |
P9423
|
FINISHED |
| Object | about 28 miles |
—
|
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: about 28 miles | Statement: [Luton Airport, distanceFromLondonCentre, about 28 miles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromLondonCentre Context triple: [Luton Airport, distanceFromLondonCentre, about 28 miles]
-
A.
distanceFromCentralLondon
chosen
Indicates the spatial separation or length of travel between a given location and central London.
-
B.
distanceToLondon
Indicates the measured distance between a given entity’s location and the city of London.
-
C.
distanceFromLeeds
Indicates the spatial distance between a given entity and the location of Leeds.
-
D.
directionFromLondon
Indicates the cardinal or relative compass direction of an entity’s location when measured from London.
-
E.
distanceFromParisCenter
Indicates the measured distance between a given location and the central point of Paris.
- 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_69a4935a94308190bb92555b79032824 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4c31602b8819087a57e8d390cae7a |
completed | March 1, 2026, 10:52 p.m. |
| PD | Predicate disambiguation | batch_69a4bee0be808190a8ccac6a41851fdd |
completed | March 1, 2026, 10:34 p.m. |
Created at: March 1, 2026, 7:50 p.m.