Triple
T30229820
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thika |
E768595
|
entity |
| Predicate | distanceToNairobi |
P51265
|
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: [Thika, distanceToNairobi, about 40 kilometres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToNairobi Context triple: [Thika, distanceToNairobi, about 40 kilometres]
-
A.
distanceFromNairobi
chosen
Indicates the spatial distance between a given entity’s location and the city of Nairobi.
-
B.
distanceFromNakuru
Indicates the spatial distance measured from the reference location of Nakuru to another place or entity.
-
C.
distanceFromKampala
Indicates the measured distance between a given location and the city of Kampala.
-
D.
directionFromNairobi
Indicates the cardinal or relative compass direction in which one location lies when viewed from Nairobi.
-
E.
distanceToAmboseliNationalPark
Indicates the measured or estimated spatial distance between a given entity and Amboseli National Park.
- 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_69f2248108208190be60bf1af343ce70 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_6a01185c46f0819089b4a2ad3c3e2f33 |
completed | May 10, 2026, 11:44 p.m. |
| PD | Predicate disambiguation | batch_6a0117e19e008190870663dd45084416 |
completed | May 10, 2026, 11:42 p.m. |
Created at: April 29, 2026, 7:36 p.m.