Triple
T25620148
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kabyle people |
E642270
|
entity |
| Predicate | countryOfficialRecognitionOfLanguage |
P112296
|
FINISHED |
| Object | Algeria |
—
|
NE NERFINISHED |
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: Algeria | Statement: [Kabyle people, countryOfficialRecognitionOfLanguage, Algeria]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: countryOfficialRecognitionOfLanguage Context triple: [Kabyle people, countryOfficialRecognitionOfLanguage, Algeria]
-
A.
countryOfficialLanguageStatus
Indicates the status or role that a particular language holds as an official language within a given country.
-
B.
declaresOfficialLanguageOf
Indicates that an authority formally designates a particular language as the official language of a specified entity or jurisdiction.
-
C.
shareOfficialLanguage
Indicates that two entities have at least one official language in common.
-
D.
hasLanguageOfficial
chosen
Indicates that a language holds official status within a given entity, such as a country, region, or organization.
-
E.
hasNotableLanguageWithOfficialStatusIn
Indicates that a language holds an officially recognized and notable status within a specified jurisdiction or region.
- 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_69e77e7a96748190b10f2699041e4e43 |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69f6c1265c208190aacd2b551f8f0f82 |
completed | May 3, 2026, 3:29 a.m. |
| PD | Predicate disambiguation | batch_69f6bd2415fc81908c23c311aebce66f |
completed | May 3, 2026, 3:12 a.m. |
Created at: April 21, 2026, 5:03 p.m.