Triple
T11865533
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arrondissement of Léogâne |
E282270
|
entity |
| Predicate | hasMajorLanguageSpoken |
P2266
|
FINISHED |
| Object | Haitian Creole |
—
|
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: Haitian Creole | Statement: [Arrondissement of Léogâne, hasMajorLanguageSpoken, Haitian Creole]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMajorLanguageSpoken Context triple: [Arrondissement of Léogâne, hasMajorLanguageSpoken, Haitian Creole]
-
A.
isSpokenAsFirstLanguageBy
Indicates that a language is the primary (native) language used by a person or group for everyday communication.
-
B.
languagesSpoken
Indicates that an entity is able to communicate using one or more specified languages.
-
C.
isWidelySpokenIn
chosen
Indicates that a language is spoken by a large portion of the population across many regions or communities within a specified area.
-
D.
hasPrimaryLanguage1
Indicates that an entity’s main or most commonly used language is the specified language.
-
E.
eligibleLanguage
Indicates that a particular language satisfies the required conditions to be considered valid or allowed in a given 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_69d6ab2945d081908a5851c916cbcfb5 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8a73883508190a78b5f4ba4a220df |
completed | April 10, 2026, 7:31 a.m. |
| PD | Predicate disambiguation | batch_69d8a2589f0c8190ad82ff11acabae93 |
completed | April 10, 2026, 7:10 a.m. |
Created at: April 8, 2026, 9:43 p.m.