Triple
T23690163
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Algeciras Heliport |
E585274
|
entity |
| Predicate | distanceToCeutaByAir |
P153419
|
FINISHED |
| Object | approximately 30 km |
—
|
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 30 km | Statement: [Algeciras Heliport, distanceToCeutaByAir, approximately 30 km]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToCeutaByAir Context triple: [Algeciras Heliport, distanceToCeutaByAir, approximately 30 km]
-
A.
distanceToTaroudant_km
Indicates the physical distance, measured in kilometers, between an entity and the location Taroudant.
-
B.
distanceFromSeville
Indicates the spatial distance separating an entity from the location of Seville.
-
C.
distanceFromSantaCruzDeTenerifeKm
Indicates the distance, measured in kilometers, between an entity and Santa Cruz de Tenerife.
-
D.
distanceTo Palma de Mallorca (approximate km)
Indicates the approximate distance in kilometers between an entity’s location and Palma de Mallorca.
-
E.
distanceToMálaga
Indicates the spatial distance between a given entity and the location of Málaga.
- 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_69e249037ce0819088b149608e98f685 |
completed | April 17, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69f1b5c16af08190b2f4d126c60a7e75 |
completed | April 29, 2026, 7:39 a.m. |
| PD | Predicate disambiguation | batch_69f155d5265881908e43a9696b6a6d0f |
completed | April 29, 2026, 12:50 a.m. |
| PDg | Predicate description generation | batch_69f157cc43a881909ed2d8b0a09b5d73 |
completed | April 29, 2026, 12:58 a.m. |
Created at: April 17, 2026, 6:52 p.m.