Triple
T34552694
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sabaki River |
E887113
|
entity |
| Predicate | rankByLengthInKenya |
P179313
|
FINISHED |
| Object | one of the longest rivers in Kenya |
—
|
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: one of the longest rivers in Kenya | Statement: [Sabaki River, rankByLengthInKenya, one of the longest rivers in Kenya]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: rankByLengthInKenya Context triple: [Sabaki River, rankByLengthInKenya, one of the longest rivers in Kenya]
-
A.
rankInAfricaByLength
Indicates the position of something in an ordered list of African entities sorted by their length (e.g., size, distance, or extent).
-
B.
rankingOnMountKenyaByHeight
Indicates the relative position of something in an ordered list of items on Mount Kenya, based on their height.
-
C.
rankByLengthInWorld
Indicates ordering entities within a given world or context based on their length, from shortest to longest or vice versa.
-
D.
rankByLengthInIndia
Indicates an ordering of items based on their length specifically within the context or boundaries of India.
-
E.
rankingByLengthInChina
Indicates that entities are ordered or evaluated based on their length within the context of China.
- 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_69f349cff89081908f91e0b064f4833e |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f72028d93881909548ade51193e552 |
completed | May 3, 2026, 10:15 a.m. |
| PD | Predicate disambiguation | batch_69f71cc8074c81909ae09bea2acf1a09 |
completed | May 3, 2026, 10 a.m. |
| PDg | Predicate description generation | batch_69f71f8df5d48190944fbfbd9d573868 |
completed | May 3, 2026, 10:12 a.m. |
Created at: May 1, 2026, 2:02 a.m.