Triple
T8825506
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Government of Sri Lanka |
E210003
|
entity |
| Predicate | linkLanguagePolicy |
P54671
|
FINISHED |
| Object | English as link 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: English as link language | Statement: [Government of Sri Lanka, linkLanguagePolicy, English as link language]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: linkLanguagePolicy Context triple: [Government of Sri Lanka, linkLanguagePolicy, English as link language]
-
A.
languagePolicyType
Indicates the specific category or type of language policy that governs how languages are used, managed, or regulated in a given context.
-
B.
languagePolicyIssue
Indicates that there is a problem, conflict, or concern related to rules or practices governing language use.
-
C.
languageOfRegistrationPolicies
Indicates the language in which the registration policies are written or officially specified.
-
D.
languagePolicyRegion
Indicates that a particular language policy applies within, or is associated with, a specific geographic or administrative region.
-
E.
hasLanguagePolicyContext
chosen
Indicates that there is an associated language-related policy, rule, or regulatory context governing how language is used or managed in relation to the subject.
- 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_69ca8365b28081909e48e45e95dfc405 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc60332d208190972a8b03fbd760ee |
completed | April 1, 2026, midnight |
| PD | Predicate disambiguation | batch_69cc5c23d08481908d8c9b0ad3d1dc00 |
completed | March 31, 2026, 11:43 p.m. |
Created at: March 30, 2026, 6:46 p.m.