Triple
T8007525
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MTV Africa Music Award |
E186399
|
entity |
| Predicate | typicalCeremonyLanguage |
P2769
|
FINISHED |
| Object | English |
—
|
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 | Statement: [MTV Africa Music Award, typicalCeremonyLanguage, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalCeremonyLanguage Context triple: [MTV Africa Music Award, typicalCeremonyLanguage, English]
-
A.
languageOfCeremony
chosen
Indicates the language in which a ceremony is conducted or officially performed.
-
B.
ceremonialLanguageElement
Indicates a linguistic element that is specifically used within or associated with formal ceremonies or ritual contexts.
-
C.
typicalLanguages
Indicates the languages that are commonly or characteristically used, spoken, or associated with a given entity.
-
D.
hasPublicCeremony
Indicates that a public ceremony is held or conducted in relation to the subject entity.
-
E.
typicalLanguageOfReadings
Indicates the language that is most commonly used for readings or interpretations associated with a given entity.
- 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_69ca82abaffc8190ab8af79cdbc31ab3 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb3cf8a6048190970685a83fd2f59d |
completed | March 31, 2026, 3:18 a.m. |
| PD | Predicate disambiguation | batch_69cb048c9f488190b4fb8917a9c21bc5 |
completed | March 30, 2026, 11:17 p.m. |
Created at: March 30, 2026, 5:18 p.m.