Triple
T36489636
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | WMT English-French dataset |
E899019
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | machine translation benchmark |
C13033
|
CONCEPT FINISHED |
How this triple was built (1 step)
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.
CD
Concept disambiguation
gpt-5-mini-2025-08-07
Target class: machine translation benchmark Context triple: [WMT English-French dataset, instanceOf, machine translation benchmark]
-
A.
benchmark in artificial intelligence
chosen
A benchmark in artificial intelligence is a standardized task, dataset, or evaluation protocol used to quantitatively compare and assess the performance of AI models and algorithms.
-
B.
translation API
A translation API is a service interface that programmatically converts text or speech from one language to another, often providing features like language detection, formatting preservation, and support for multiple translation models.
-
C.
translation institute
A translation institute is an organization dedicated to providing professional language translation and interpretation services, training translators, and promoting standards and research in the field of translation.
-
D.
translation
Translation is the process of converting text or speech from one language into another while preserving its meaning, tone, and context.
-
E.
bilingual dataset
A bilingual dataset is a structured collection of aligned or comparable data in two different languages, typically used for tasks like machine translation, cross-lingual learning, or linguistic analysis.
- F. None of above.
Provenance (1 batch)
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_69f76e5ad4588190bdbce60c52fbb785 |
completed | May 3, 2026, 3:48 p.m. |
Created at: May 3, 2026, 4:10 p.m.