Triple
T3000923
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mount Kenya |
E81182
|
entity |
| Predicate | nearCity |
P350
|
FINISHED |
| Object |
Nanyuki
Nanyuki is a Kenyan town on the equator that serves as a popular gateway to Mount Kenya and the surrounding highland wilderness.
|
E324393
|
NE FINISHED |
How this triple was built (4 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: Nanyuki | Statement: [Mount Kenya, nearCity, Nanyuki]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nanyuki Context triple: [Mount Kenya, nearCity, Nanyuki]
-
A.
Nungua
Nungua is a coastal town and suburb of Accra in southern Ghana, known for its fishing community and vibrant local culture.
-
B.
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.
-
C.
Ngong River
Ngong River is a tributary watercourse in Kenya that flows through parts of Nairobi’s urban and peri-urban areas before joining the Nairobi River system.
-
D.
Lake Naivasha
Lake Naivasha is a freshwater lake in Kenya’s Great Rift Valley, renowned for its rich birdlife, hippo populations, and surrounding flower farms and wildlife conservancies.
-
E.
Kisumu
Kisumu is a major Kenyan city on the shores of Lake Victoria, serving as a key commercial and transport hub in western Kenya.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Nanyuki Triple: [Mount Kenya, nearCity, Nanyuki]
Generated description
Nanyuki is a Kenyan town on the equator that serves as a popular gateway to Mount Kenya and the surrounding highland wilderness.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Nanyuki Target entity description: Nanyuki is a Kenyan town on the equator that serves as a popular gateway to Mount Kenya and the surrounding highland wilderness.
-
A.
Nungua
Nungua is a coastal town and suburb of Accra in southern Ghana, known for its fishing community and vibrant local culture.
-
B.
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.
-
C.
Ngong River
Ngong River is a tributary watercourse in Kenya that flows through parts of Nairobi’s urban and peri-urban areas before joining the Nairobi River system.
-
D.
Lake Naivasha
Lake Naivasha is a freshwater lake in Kenya’s Great Rift Valley, renowned for its rich birdlife, hippo populations, and surrounding flower farms and wildlife conservancies.
-
E.
Kisumu
Kisumu is a major Kenyan city on the shores of Lake Victoria, serving as a key commercial and transport hub in western Kenya.
- F. None of above. chosen
Provenance (5 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_69ad8b187fc8819085914d3c9ea3142d |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad9a1022e48190afee77db94635ff2 |
completed | March 8, 2026, 3:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b1f8629c7c8190b597255ab8f391af |
completed | March 11, 2026, 11:18 p.m. |
| NEDg | Description generation | batch_69b1f8e5cdd08190840321d7ad1fe1e2 |
completed | March 11, 2026, 11:21 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b1f968f17c81908b1e96f482546b80 |
completed | March 11, 2026, 11:23 p.m. |
Created at: March 8, 2026, 2:59 p.m.