Triple
T37922102
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | COSMAS II corpus search system |
E945990
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | language resource infrastructure component |
C34934
|
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: language resource infrastructure component Context triple: [COSMAS II corpus search system, instanceOf, language resource infrastructure component]
-
A.
research infrastructure component
chosen
A research infrastructure component is a foundational hardware, software, or service element that supports the collection, storage, processing, and sharing of data and tools necessary for conducting and advancing research.
-
B.
linguistic archive
A linguistic archive is a curated, long-term repository that collects, preserves, and provides access to language data and related documentation in various formats for research, revitalization, and educational purposes.
-
C.
R infrastructure component
An R infrastructure component is a foundational element—such as runtime, package system, or tooling—that supports the execution, management, and scalability of R-based data analysis and applications.
-
D.
language museum
A language museum is a curated space, physical or virtual, that preserves, exhibits, and interprets the history, diversity, structure, and cultural significance of human languages.
-
E.
language preservation area
A language preservation area is a designated region or community space where policies, resources, and activities are focused on maintaining, revitalizing, and transmitting one or more endangered or minority languages.
- 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_69f76ef2ebd88190be5229f2621070b3 |
completed | May 3, 2026, 3:51 p.m. |
Created at: May 3, 2026, 4:20 p.m.