Triple
T11014330
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kilimanjaro International Airport |
E260324
|
entity |
| Predicate | distanceToMoshi |
P96999
|
FINISHED |
| Object | about 40 kilometres |
—
|
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 40 kilometres | Statement: [Kilimanjaro International Airport, distanceToMoshi, about 40 kilometres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToMoshi Context triple: [Kilimanjaro International Airport, distanceToMoshi, about 40 kilometres]
-
A.
distanceFromHanaTown (miles)
Indicates the number of miles separating a given place or entity from Hana Town.
-
B.
distanceFromMiyakoAirport
Indicates the measured distance between a given location and Miyako Airport.
-
C.
distanceFromTokyo
Indicates the physical distance between a given location and Tokyo.
-
D.
hasApproximateDrivingDistanceFrom
Indicates that one entity is located at an estimated or approximate driving distance from another entity, typically measured along road routes rather than as a precise or exact value.
-
E.
distanceToIōtō
Indicates the spatial distance between a subject and the location Iōtō.
- 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_69d6aa9687448190b28d353b1b6a610e |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d797a49f648190a5144625d09dec6f |
completed | April 9, 2026, 12:12 p.m. |
| PD | Predicate disambiguation | batch_69d72e96be6c8190a46c69f61b2d8cd4 |
completed | April 9, 2026, 4:44 a.m. |
| PDg | Predicate description generation | batch_69d733b27ffc81908ab1b8df198cd5c7 |
completed | April 9, 2026, 5:05 a.m. |
Created at: April 8, 2026, 9:25 p.m.