proofreading edits

Made proofreading edits.

docs/eml-semantic-annotations-primer.md

@@ -44,14 +44,13 @@ Here is an example of an `attribute` element containing 2 annotations:
 </attribute>
 ```
 
-In the above example, the first annotation has the subject the attribute with id "1234", the object property "http://ecoinformatics.org/oboe/oboe.1.2/oboe-core.owl#containsMeasurementsOfType", and the object "http://purl.dataone.org/odo/ECSO_00001125". After serializing the EML into a semantic web format, such as RDF or JSON-LD, the system could interpret the semantic statement as "the attribute with id '1234' contains measurements of types of dissolved organic carbon concentration".
-
-The second annotation has the subject the attribute with id "1234", the object property "http://ecoinformatics.org/oboe/oboe.1.2/oboe-core.owl#hasUnit", and the object "http://purl.obolibrary.org/obo/UO_0000273". The semantic statement associated with this triple can be read as "the attribute with the id '1234' has units of milligram per liter".
+In the above example, the first annotation has as the subject the attribute with id "1234", the object property "http://ecoinformatics.org/oboe/oboe.1.2/oboe-core.owl#containsMeasurementsOfType", and the object "http://purl.dataone.org/odo/ECSO_00001125". After serializing the EML into a semantic web format, such as RDF or JSON-LD, the system could interpret the semantic statement as "the attribute with id '1234' contains measurements of types of dissolved organic carbon concentration".
 
+The second annotation has as the subject the attribute with id "1234", the object property "http://ecoinformatics.org/oboe/oboe.1.2/oboe-core.owl#hasUnit", and the object "http://purl.obolibrary.org/obo/UO_0000273". The semantic statement associated with this triple can be read as "the attribute with the id '1234' has units of milligram per liter".
 
 #### Dataset-level annotations
 
-A dataset can be (and often is) composed of a series of data entities (see 'entity-level annotation' section below) that are linked together by particular integrity constraints. The `dataset` element encompasses all information about a single dataset. It is intended to provide overview information about the dataset: broad information such as the title, abstract, keywords, contacts, maintenance history, purpose, and distribution of the data themselves. Dataset-level metadata describes a data collection event. This event may take place over some period of time and include many actual collections (e.g. a time series or remote sensing application) or it could be just one actual collection (e.g. a day in the field). Further information about datasets may be found in the "eml-dataset module" section in chapter 5.3.
+A dataset can be (and often is) composed of a series of data entities (see 'entity-level annotations' section below) that are linked together by particular integrity constraints. The `dataset` element encompasses all information about a single dataset. It is intended to provide overview information about the dataset: broad information such as the title, abstract, keywords, contacts, maintenance history, purpose, and distribution of the data themselves. Dataset-level metadata describes a data collection event. This event may take place over some period of time and include many actual collections (e.g. a time series or remote sensing application) or it could be just one actual collection (e.g. a day in the field). Further information about datasets may be found in the "eml-dataset module" section in chapter 5.3.
 
 A dataset-level annotation represents a precisely-defined semantic statement that applies to a dataset. This semantic statement is used to associate precise measurement semantics with the dataset. A dataset-level `annotation` element is embedded in a containing `dataset` element. The subject of the semantic statement is the `dataset` element that contains the annotation. If the `dataset` element contains an `id` attribute, then the subject should be the value of the `id` attribute. Each annotation consists of a `propertyURI` element and `valueURI` element, which respectively define a property and a value (object) that apply to the dataset. Each URI should resolve to a controlled vocabulary that provides a precise definition, relationships to other terms, and multiple labels for displaying the statement. The associated `label` attribute for each URI can be used to display the property and value in a more readable format to users. Ideally, each `label` should be populated by a preferred label or label from a controlled vocabulary.