Triple
T33847564
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eritrean languages |
E867524
|
entity |
| Predicate | hasOfficialWorkingLanguage |
P117460
|
FINISHED |
| Object | Tigrinya |
—
|
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: Tigrinya | Statement: [Eritrean languages, hasOfficialWorkingLanguage, Tigrinya]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOfficialWorkingLanguage Context triple: [Eritrean languages, hasOfficialWorkingLanguage, Tigrinya]
-
A.
hasOfficialLanguageOfWork
chosen
Indicates that an entity uses a specified language as its official medium for conducting work or formal activities.
-
B.
hasOfficialCountryLanguage
Indicates that a country recognizes a particular language as one of its official languages for governmental or legal purposes.
-
C.
hasOfficialLanguageOfLocation
Indicates that a location has a specified language recognized as its official language.
-
D.
usesOfficialLanguageOf
Indicates that one entity adopts and employs the official language of another entity for communication or formal purposes.
-
E.
hasLanguageOfficial
Indicates that a language holds official status within a given entity, such as a country, region, or organization.
- 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_69f349937b648190a34ada70f6a2b534 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f7b2f3a104819098ddd8909eaf596c |
completed | May 3, 2026, 8:41 p.m. |
| PD | Predicate disambiguation | batch_69f7b1b8a9fc8190a1279e67a2d12707 |
completed | May 3, 2026, 8:36 p.m. |
Created at: May 1, 2026, 1:47 a.m.