Triple
T14082834
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Litunga |
E338908
|
entity |
| Predicate | linguaFrancaOfCourt |
P24056
|
FINISHED |
| Object | Silozi |
—
|
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: Silozi | Statement: [Litunga, linguaFrancaOfCourt, Silozi]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: linguaFrancaOfCourt Context triple: [Litunga, linguaFrancaOfCourt, Silozi]
-
A.
languageOfJurisdiction
Indicates the language officially used for legal and administrative purposes within a given jurisdiction.
-
B.
isLinguaFrancaOf
chosen
Indicates that a language serves as a common medium of communication between speakers of different native languages within a particular region, community, or context.
-
C.
standardLanguageOf
Indicates that one entity serves as the officially recognized or commonly used standard language for another entity (such as a country, region, or organization).
-
D.
officialLanguage
Indicates that a particular language has been formally designated by an authority as the official language used for government, legal, or administrative purposes in a given jurisdiction.
-
E.
courtLanguage
Indicates the language officially used in legal proceedings or by a court.
- 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_69d81c687b0c819087fd9ed4198403f8 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de5ede40048190b465e909565730c1 |
completed | April 14, 2026, 3:35 p.m. |
| PD | Predicate disambiguation | batch_69de05b0e6c88190a819eeba0028981f |
completed | April 14, 2026, 9:15 a.m. |
Created at: April 9, 2026, 10:21 p.m.