Triple
T34219134
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ethiopia–Djibouti border |
E877875
|
entity |
| Predicate | languageRegionsAffected |
P29819
|
FINISHED |
| Object | Afar language |
—
|
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: Afar language | Statement: [Ethiopia–Djibouti border, languageRegionsAffected, Afar language]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageRegionsAffected Context triple: [Ethiopia–Djibouti border, languageRegionsAffected, Afar language]
-
A.
languageRegionsRepresented
Indicates that certain geographic or cultural regions are represented or covered through specific languages.
-
B.
alsoInLanguageRegion
Indicates that two or more entities are located within or associated with the same language-defined geographic region.
-
C.
regionOfMajorLanguage
Indicates the geographic region where a particular language is predominantly spoken or holds major usage.
-
D.
languageArea
chosen
Indicates the geographic or cultural region in which a particular language is used or predominantly spoken.
-
E.
operatorLanguageRegion
Indicates the geographic region or locale in which an operator’s language is used or applicable.
- 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_69f349b0b4bc819088c1552424089ee9 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_6a005b2e0a9c819081c6f7ccbef49ff8 |
completed | May 10, 2026, 10:17 a.m. |
| PD | Predicate disambiguation | batch_6a005a8bcde88190ace2bc0215e26430 |
completed | May 10, 2026, 10:14 a.m. |
Created at: May 1, 2026, 1:55 a.m.