Triple
T33777937
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kipsigiis |
E865570
|
entity |
| Predicate | ageSetSystem |
P100475
|
FINISHED |
| Object | Kalenjin age-set system |
—
|
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: Kalenjin age-set system | Statement: [Kipsigiis, ageSetSystem, Kalenjin age-set system]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ageSetSystem Context triple: [Kipsigiis, ageSetSystem, Kalenjin age-set system]
-
A.
ageSystem
Indicates a relationship where one entity specifies or uses a particular system or standard for expressing age (e.g., calendar system, counting convention, or age-measurement method) for another entity.
-
B.
ageSetting
Indicates that one entity specifies, adjusts, or defines the age value or age-related parameter of another entity.
-
C.
ageGroupSystem
chosen
Indicates a classification relationship where entities are grouped according to a defined system of age-based categories.
-
D.
ageType
Indicates the specific categorization or classification of an age value (e.g., actual, estimated, range-based) associated with an entity.
-
E.
ageModel
Indicates a relationship where one entity specifies or provides the age of another entity, typically in terms of a particular age value or age-related classification.
- 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_69f3498df6f88190bf9647ea4e4a956e |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f6ffbad8848190867c2988c0ceb84f |
completed | May 3, 2026, 7:56 a.m. |
| PD | Predicate disambiguation | batch_69f6fc5740fc81909774a4f65201a3ff |
completed | May 3, 2026, 7:42 a.m. |
Created at: May 1, 2026, 1:45 a.m.