Triple
T17519839
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | websockets |
E426654
|
entity |
| Predicate | hostLanguageEcosystem |
P75919
|
FINISHED |
| Object | Python async ecosystem |
—
|
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: Python async ecosystem | Statement: [websockets, hostLanguageEcosystem, Python async ecosystem]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hostLanguageEcosystem Context triple: [websockets, hostLanguageEcosystem, Python async ecosystem]
-
A.
languageOfEnvironment
Indicates the language predominantly used or present in a given environment or context.
-
B.
languagesUsed
Indicates that one entity uses, employs, or is expressed in one or more languages associated with the other entity.
-
C.
developedForLanguage
chosen
Indicates that something (such as a tool, system, or resource) was specifically created or adapted to be used with a particular language.
-
D.
languageAssociation
Indicates an association or relationship between entities based on a language they use, represent, or are linked to.
-
E.
projectLanguageCode
Indicates the programming or markup language used in a project, represented by its standardized language code.
- 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_69d889de677081909b22d2657b1f0292 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e452d18c1c81908bb843bbddb44ca1 |
completed | April 19, 2026, 3:58 a.m. |
| PD | Predicate disambiguation | batch_69e3b4f8b9888190aa8a45e09acf4319 |
completed | April 18, 2026, 4:44 p.m. |
Created at: April 10, 2026, 5:49 a.m.