Triple
T34942953
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vale do Lobo resort |
E1007774
|
entity |
| Predicate | distanceFromFaroAirport |
P205620
|
FINISHED |
| Object | approximately 20 kilometers |
—
|
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 20 kilometers | Statement: [Vale do Lobo resort, distanceFromFaroAirport, approximately 20 kilometers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromFaroAirport Context triple: [Vale do Lobo resort, distanceFromFaroAirport, approximately 20 kilometers]
-
A.
distanceFromKeflavíkAirport
Indicates the measured distance between a given location and Keflavík Airport.
-
B.
distance to Tórshavn (kilometers)
Indicates the length, in kilometers, of the shortest travel distance between an entity and the location Tórshavn.
-
C.
distanceFromReykjavík
Indicates the spatial distance between an entity’s location and the city of Reykjavík.
-
D.
distanceFromArendal
Indicates the spatial distance between a given entity and the location of Arendal.
-
E.
distanceFromKristiansand
Indicates the spatial distance between a given location or object and the city of Kristiansand.
- 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_69f76dc513fc819084a1ff52abbfa5bc |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_6a037c92f03c8190ae2751270b195423 |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379ff1ba081908eda86acefcf69fb |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c80ba448190853011097a151b7e |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 3, 2026, 4 p.m.