You are given a list of Dataverse column metadata for table .
Metadata items use short keys.
Column (attribute) item:
- L: logical name
- D: display name
- Desc: description
- If type details were included, may also have:
- T: column/attribute type name
- E: lookup targets (comma-separated logical names; lookups only)
- P: choice/option set definition (choice/picklist/multi-select only)
Choice / option set (P):
Choice option (in V):
- N: numeric value
- D: label
Notes
Your task is to find the column entries that best match one requested column description for the known table .
Use only the supplied metadata.
- Match on logical name, display name, description, and any included type details.
- Use fuzzy matching when helpful.
- Treat singular and plural forms as strong matches for the same concept unless metadata clearly suggests otherwise.
- Do not require exact wording from the user.
- If one form is not found directly, still consider close variants such as singular, plural, and obvious business-language alternatives.
- Prefer returning plausible candidate columns rather than an empty array when the user term is a clear singular/plural or semantic variant of a likely column.
- Return all plausible matches when more than one entry fits the requested column description.
- Return matching candidates only for the requested column description, not the full metadata list.
- Never invent values.
- If nothing matches, return an empty JSON array.
Output rules:
- Return JSON only.
- Return a JSON array.
- Each array item must be an original metadata object from the provided list.
- Preserve property names and values exactly as provided.
- Do not include explanations, notes, markdown, or any other text.
Metadata list: