Triple
T31768153
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Samia |
E810863
|
entity |
| Predicate | countryStatusInKenya |
P199131
|
FINISHED |
| Object | minority language |
—
|
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: minority language | Statement: [Samia, countryStatusInKenya, minority language]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: countryStatusInKenya Context triple: [Samia, countryStatusInKenya, minority language]
-
A.
statusInKenya
chosen
Indicates the legal, social, or official standing or condition that an entity holds specifically within the context of Kenya.
-
B.
countryStatus
Indicates the political or legal condition of a country, such as its sovereignty, recognition, or current state in international or domestic contexts.
-
C.
majorAreasKenya
Indicates that the related entities represent the principal geographic or administrative regions within Kenya.
-
D.
rankByLengthInKenya
Indicates ordering or comparing entities based on their length specifically within the context or boundaries of Kenya.
-
E.
countrySpecificStatus
Indicates a status or condition that is defined or applied specifically in the context of a particular country.
- 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_69f348e463e08190b902d4819195e1f0 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_6a000014497c819088d5cda3977522dd |
completed | May 10, 2026, 3:48 a.m. |
| PD | Predicate disambiguation | batch_69ffff9a52b08190be1024e0fb6fe661 |
completed | May 10, 2026, 3:46 a.m. |
Created at: April 30, 2026, 11:33 p.m.