Merge branch 'vector-db' of github.com:ezimuel/semantic-conventions i…

…nto vector-db

model/database/spans.yaml

@@ -803,34 +803,34 @@ groups:
           If the query doesn't target a specific index, this field MUST NOT be set.
         examples: ['my_index', 'index1, index2']
       - ref: db.search.similarity_metric
-        brief: specify the metric used in similarity search (e.g. cosine)
+        brief: Specifies the metric used in similarity search (e.g. cosine)
         note: >
           Some vector databases allow specifying the similarity search during a search, while others only allow it when creating an index or collection.
         requirement_level:
           conditionally_required: If available.
         examples: ['cosine', 'dot', 'euclidean', 'manhattan']
       - ref: db.record.id
-        brief: the ID of the record (e.g. the ID of the vector)
+        brief: The ID of the record (e.g. the ID of the vector)
         note: >
           Some vector databases identify a vector using an ID.
         requirement_level:
           conditionally_required: If available.
         examples: ['1', '5c56c793-69f3-4fbf-87e6-c4bf54c28c26']
       - ref: db.vector.field_name
-        brief: the name field of the vector embedding
+        brief: The name field of the vector embedding
         note: >
           Some vector databases use a field name to store the vector.
         requirement_level:
           conditionally_required: If available.
         examples: ['image_vector', 'embedding_field']
       - ref: db.vector.dimension_count
-        brief: the dimension of the vector (e.g. 1536)
+        brief: The dimension of the vector (e.g. 1536)
         note: >
           The dimension of a vector is typically defined when building an index/collection.
         requirement_level: recommended
         examples: [3, 1536]
       - ref: db.vector.query.top_k
-        brief: the top-k most similar vectors returned by a query
+        brief: The top-k most similar vectors returned by a query
         note: >
           The top-k parameter is usually specified when executing a vector search (i.e. query)
         requirement_level: