fixup spelling

doc/annotation_creation.md

@@ -47,7 +47,7 @@ semehr_annotate.sh -i anon_dir/ -o annot_dir/
 
 ## DICOM SR annotation
 
-This is simlar to Standalone document annotation but with a preceding
+This is similar to Standalone document annotation but with a preceding
 step of extracting the text from a DICOM file. Also supported is
 extracting the text from a MongoDB database (where the tags are stored
 in SMI format).

doc/annotation_database.md

@@ -170,7 +170,7 @@ Pass = 'semehr'
 DatabaseName = 'semehr'
 Schema = 'semehr'
 Table = 'semehr_results'
-# Connecto to database
+# Connect to database
 pgConnection = psycopg2.connect(host=Host, user=User, password=Pass, dbname=DatabaseName)
 # Search for all documents having an annotation where featurename = "cui" featureval = "C0175252"
 query_obj = [ { featurename: featureval, 'Negation': 'Affirmed' } ]
@@ -280,7 +280,7 @@ but is indexed as a PostgreSQL date so it can be searched.
 The annotations array has elements like this:
 * `start`, `end`, the character offsets into `redacted_text`
 * `str`, the original text string
-* `id`, an indentifier for this annotation
+* `id`, an identifier for this annotation
 * `negation`, whether affirmed or negated
 * `temporality`, whether recent or historical
 * `experiencer`, whether the patient or other

doc/anonymisation.md

@@ -127,7 +127,7 @@ Rule document structure
 ```
 
 The `general data structure` of an atom rule.
-```javscript
+```javascript
 
 "RULE_NAME": {
     "pattern": "REGULAR_EXPRESSION_(WITH_GROUPS)", 

doc/tools.md

@@ -424,7 +424,7 @@ Pass = 'semehr'
 DatabaseName = 'semehr'
 Schema = 'semehr'
 Table = 'semehr_results'
-# Connecto to database
+# Connect to database
 pgConnection = psycopg2.connect(host=Host, user=User, password=Pass, dbname=DatabaseName)
 # Search for all documents having an annotation where featurename = "cui" featureval = "C0175252"
 query_obj = [ { featurename: featureval, 'Negation': 'Affirmed' } ]
@@ -493,7 +493,7 @@ but is indexed as a PostgreSQL date so it can be searched.
 The annotations array has elements like this:
 * `start`, `end`, the character offsets into `redacted_text`
 * `str`, the original text string
-* `id`, an indentifier for this annotation
+* `id`, an identifier for this annotation
 * `negation`, whether affirmed or negated
 * `temporality`, whether recent or historical
 * `experiencer`, whether the patient or other

doc/umls_metathesaurus.md

@@ -200,7 +200,7 @@ snomed|cui
 
 Describes a Semantic Type. The identifier TUI is a member of a group of similar
 types tuigroup, and the group has a label tuigrouplabel. This is used to find out
-if a concept is related to other concepts that also share a simlar Semantic Type,
+if a concept is related to other concepts that also share a similar Semantic Type,
 i.e. their types are both members of the same Semantic Group.
 
 ```

src/applications/semehr_anon.py

@@ -9,7 +9,7 @@
 # so use the -a (--all) option to write all the others too.
 # To anonymise *DICOM* files you need CTP_SRAnonTool.sh
 # (which uses CTP_DicomToText, this script, and CTP_XMLToDicom).
-# NOTE: this script has superceded semehr_anon.sh.
+# NOTE: this script has supersceded semehr_anon.sh.
 
 import argparse, json, logging, re, sys, os, glob
 from logging import handlers

src/tools/semehr_anon.sh

@@ -6,7 +6,7 @@
 # To anonymise *DICOM* files you need CTP_SRAnonTool.sh.
 # NOTE: this script uses several external programs:
 #   jq, CTP_PhiToXML.py, semehr_redact.py
-# NOTE: this script has been superceded by semehr_anon.py.
+# NOTE: this script has been supersceded by semehr_anon.py.
 
 prog="$0"
 usage="usage: $prog [-s semehr_dir] -i input -o output"

src/tools/semehr_to_mongo.py

@@ -287,7 +287,7 @@ def mongo_query_feature(featurename, featureval):
     # OLD x = mongoCursor = mongoCollection.find( { "Mention" : { "$elemMatch": { "features."+featurename : featureval } } } )
     # NOW x = mongoCursor = mongoCollection.find( { "annotations" : { "$elemMatch": { featurename : featureval } } } )
     # append .count()  to get just the number of results
-    # append .explain() to get the query explaination
+    # append .explain() to get the query explanation
     # append .explain()['executionStats']
     # Query for annotations which have the feature AND are negated/affirmed
     query_obj = { featurename : featureval, 'negation':'Negated' }