Triple
T7085582
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eldoret International Airport |
E165065
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | Eldoret |
E405321
|
NE 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: Eldoret | Statement: [Eldoret International Airport, locatedNear, Eldoret]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Eldoret Context triple: [Eldoret International Airport, locatedNear, Eldoret]
-
A.
Eldoret
chosen
Eldoret is a major town in western Kenya known as an agricultural and commercial hub and as a center for world-class long-distance runners.
-
B.
Kisumu
Kisumu is a major Kenyan city on the shores of Lake Victoria, serving as a key commercial and transport hub in western Kenya.
-
C.
Nakuru
Nakuru is a prominent Kenyan city in the Rift Valley region, known for its proximity to Lake Nakuru National Park and its role as an important agricultural and commercial center.
-
D.
Embakasi
Embakasi is a residential and industrial area in Nairobi, Kenya, known for hosting key infrastructure and serving as a major gateway corridor to the city.
-
E.
Kericho District
Kericho District was a former administrative district in Kenya’s Rift Valley Province, known primarily for its extensive tea plantations and cool highland climate.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69c6887d98408190912b9580666b0c1d |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e512bda88190920ecb54b177e569 |
completed | March 27, 2026, 8:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7a31c26808190870e6bcdef45d1d7 |
completed | March 28, 2026, 9:45 a.m. |
Created at: March 27, 2026, 2:41 p.m.