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Disclaimer for Advanced Users
(See disclaimer for
"general" users)
A number of analyses on this site -- including collocate grouping,
pattern classification, and descriptive summaries -- incorporate the use
of large language models (LLMs) such as GPT, Gemini, or Claude. These
systems have been integrated not to replace expert analysis, but to
offer approximate, accessible
overviews grounded in corpus data.
We
recognize and address several common concerns:
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Intended Audience and
Scope: The LLM-generated insights are primarily intended
for non-native speakers
and language learners,
who often lack the tools or training to independently extract
patterns from corpus output. Expecting expert-level linguistic
analysis -- particularly within the 250–300 word constraints imposed
by most of the API prompts at this site -- sets an unrealistic
benchmark for what these tools are designed to achieve.
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Complementary Function:
These outputs function as
interpretive scaffolds -- not definitive claims, but
preliminary summaries that help users make sense of unfamiliar data.
Advanced users are encouraged to treat them as heuristic entry
points, not as substitutes for close corpus-based investigation.
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On Criticism and Scholarly
Standards: It is methodologically unsound to highlight only
the subset of LLM outputs that are weak or inaccurate in order to
discredit the tool as a whole. A more rigorous evaluation involves
selecting a representative or randomized sample and reporting
meaningful performance metrics -- e.g., the percentage of responses
that are insightful, vague, or misleading.
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Constructive Evaluation
Welcome: We welcome empirical critiques and suggestions for
improvement -- especially when these are grounded in an
understanding of corpus methodologies and realistic expectations for
LLM output.
In short:
the LLM-based analyses are useful in context, especially for helping
learners engage with linguistic data. For expert users, they are meant
to complement (not compete
with) traditional corpus analysis, offering efficient approximations
that can be further refined through human expertise.
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