Triple
T2669629
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nigerian Pidgin |
E55717
|
entity |
| Predicate | hasExampleWord |
P4548
|
FINISHED |
| Object | waka |
—
|
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: waka | Statement: [Nigerian Pidgin, hasExampleWord, waka]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasExampleWord Context triple: [Nigerian Pidgin, hasExampleWord, waka]
-
A.
hasExample
Indicates that one entity serves as an instance, illustration, or concrete example of another entity.
-
B.
hasNonExample
Indicates that something is associated with an instance that explicitly does not satisfy or illustrate a given concept, rule, or category.
-
C.
hasWordForHello
Indicates that a language or entity possesses a specific word or expression used to say "hello" or greet.
-
D.
hasRootWord
Indicates that one linguistic form is derived from, based on, or directly associated with a specified root word.
-
E.
hasNotableWord
chosen
Indicates that an entity is associated with a word or term that is considered notable, distinctive, or significant in some context.
- 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_69ab49e54de48190be708cd1cf8be073 |
completed | March 6, 2026, 9:40 p.m. |
| NER | Named-entity recognition | batch_69abd98d32ac8190b8edd9421b706532 |
completed | March 7, 2026, 7:53 a.m. |
| PD | Predicate disambiguation | batch_69abd8190ad481908f3e14ac84d0940a |
completed | March 7, 2026, 7:47 a.m. |
Created at: March 6, 2026, 9:54 p.m.