Triple
T7349166
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Calais-Dunkerque Airport |
E169449
|
entity |
| Predicate | distanceFromDunkirk |
P76743
|
FINISHED |
| Object | approximately 40 km west |
—
|
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: approximately 40 km west | Statement: [Calais-Dunkerque Airport, distanceFromDunkirk, approximately 40 km west]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromDunkirk Context triple: [Calais-Dunkerque Airport, distanceFromDunkirk, approximately 40 km west]
-
A.
distanceToFolkestone
Indicates the spatial distance between a given location or entity and the town of Folkestone.
-
B.
distanceToUtahBeach
Indicates the spatial distance between a given entity and Utah Beach.
-
C.
distanceToSunderland_km
Indicates the physical distance, measured in kilometers, between a given place and Sunderland.
-
D.
distanceToSaintHelena
Indicates the measured distance between a given entity and the location of Saint Helena.
-
E.
distanceFromSunderland
Indicates the spatial distance between a given entity and the location of Sunderland.
- F. None of above. chosen
Provenance (4 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_69c68a5878888190968ce4d04db8d69f |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f139505c8190a7158cf59a6e089e |
completed | March 27, 2026, 9:06 p.m. |
| PD | Predicate disambiguation | batch_69c6f02aeeb8819099d1626566cec18b |
completed | March 27, 2026, 9:01 p.m. |
| PDg | Predicate description generation | batch_69c6f1379cac81908b35e617c44c7b13 |
completed | March 27, 2026, 9:05 p.m. |
Created at: March 27, 2026, 3:05 p.m.