Triple
T6771954
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Atlantic English Creole |
E155063
|
entity |
| Predicate | hasSubstrateLanguages |
P11299
|
FINISHED |
| Object | West African languages |
—
|
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: West African languages | Statement: [Atlantic English Creole, hasSubstrateLanguages, West African languages]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSubstrateLanguages Context triple: [Atlantic English Creole, hasSubstrateLanguages, West African languages]
-
A.
hasSubstrateLanguage
chosen
Indicates a relationship where one language serves as the underlying substrate that has influenced or shaped another language.
-
B.
hasSubLanguage
Indicates that one language is a subset, variant, or specialized form of another language.
-
C.
hasLanguages
Indicates that an entity is associated with one or more languages it uses, supports, or is expressed in.
-
D.
hasLanguageType
Indicates that an entity is associated with a particular type or category of language (e.g., spoken, written, programming, sign).
-
E.
hasProtoLanguage
Indicates that a language or language family originates from, or is derived from, a specified proto-language.
- 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_69c68812ef7c819099369f51febb725c |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d2496fa08190895d8b625fb0d699 |
completed | March 27, 2026, 6:54 p.m. |
| PD | Predicate disambiguation | batch_69c6d094105881909c5806eb4afa6306 |
completed | March 27, 2026, 6:46 p.m. |
Created at: March 27, 2026, 2:13 p.m.