Triple
T1332438
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sranan |
E28672
|
entity |
| Predicate | superstrateLanguage |
P27850
|
FINISHED |
| Object | English language |
—
|
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 language | Statement: [Sranan, superstrateLanguage, English language]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: superstrateLanguage Context triple: [Sranan, superstrateLanguage, English language]
-
A.
hasSubstrateLanguage
Indicates a relationship where one language serves as the underlying substrate that has influenced or shaped another language.
-
B.
scriptVariantLanguage
Indicates that a language is a variant distinguished by its writing system or script from another, related language form.
-
C.
languageFeature
Indicates that one entity is a characteristic, property, or capability of a language associated with the other entity.
-
D.
programmingLanguage
Indicates that one entity is a programming language used to create, control, or interact with the other entity.
-
E.
hasLanguageOn
Indicates that an entity uses or is associated with a particular language in a specific context, medium, or location.
- F. None of above. chosen
Provenance (4 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_69a498561a508190a3e1bc137c2b866a |
completed | March 1, 2026, 7:49 p.m. |
| NER | Named-entity recognition | batch_69a4c1e7f1388190a6e4eb65a7997380 |
completed | March 1, 2026, 10:47 p.m. |
| PD | Predicate disambiguation | batch_69a4bef174708190a07bbc697fe19a2d |
completed | March 1, 2026, 10:34 p.m. |
| PDg | Predicate description generation | batch_69a4c1bf31988190a659f48fe018f4bc |
completed | March 1, 2026, 10:46 p.m. |
Created at: March 1, 2026, 7:55 p.m.