Triple
T38619827
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kharan |
E936836
|
entity |
| Predicate | hasNationalLanguageCountry |
P95654
|
FINISHED |
| Object | English |
—
|
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: English | Statement: [Kharan, hasNationalLanguageCountry, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNationalLanguageCountry Context triple: [Kharan, hasNationalLanguageCountry, English]
-
A.
hasDeFactoNationalLanguageCountry
Indicates that a country has a language which functions as its de facto national language, even if not legally designated as such.
-
B.
hasOfficialCountryLanguage
chosen
Indicates that a country recognizes a particular language as one of its official languages for governmental or legal purposes.
-
C.
hasLanguageInCountry
Indicates that a particular language is used or recognized within a specified country.
-
D.
hasNotableLanguageWithOfficialStatusIn
Indicates that a language holds an officially recognized and notable status within a specified jurisdiction or region.
-
E.
hasLanguageOfSurroundingCountries
Indicates that an entity uses or includes the languages commonly spoken in the countries that geographically surround it.
- 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_69f76ed403208190b862dc795171353f |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fff328ddc0819080642334a41fcf95 |
completed | May 10, 2026, 2:53 a.m. |
| PD | Predicate disambiguation | batch_69fff2e0971c819081aa66f4a6a34b28 |
completed | May 10, 2026, 2:52 a.m. |
Created at: May 3, 2026, 4:32 p.m.