Triple
T10021188
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Athi River settlements |
E200611
|
entity |
| Predicate | hasUrbanChallenge |
P32029
|
FINISHED |
| Object | informal settlements |
—
|
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: informal settlements | Statement: [Athi River settlements, hasUrbanChallenge, informal settlements]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasUrbanChallenge Context triple: [Athi River settlements, hasUrbanChallenge, informal settlements]
-
A.
hasUrbanIssue
chosen
Indicates that an entity experiences, is affected by, or is associated with a specific problem or challenge related to urban environments or city life.
-
B.
hasChallenge
Indicates that an entity faces, experiences, or is confronted with a particular difficulty, obstacle, or problem.
-
C.
hasUrbanFeature
Indicates that a place or area possesses a specific urban element or infrastructure feature (such as roads, parks, or buildings) as part of its built environment.
-
D.
hasUrbanFabric
Indicates that one entity possesses, contains, or is characterized by a particular pattern or structure of built-up urban development.
-
E.
hasUrbanAccess
Indicates that an entity has access to urban areas, services, or infrastructure.
- 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_69ca831c45f08190ac1505cc15076608 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cdcd79485881909df562bfff36ccf4 |
completed | April 2, 2026, 1:59 a.m. |
| PD | Predicate disambiguation | batch_69cd4b7cd4208190b2253583ee2f892c |
completed | April 1, 2026, 4:44 p.m. |
Created at: March 30, 2026, 8:53 p.m.