chg: rebuilt the dataset

README.md

@@ -1,14 +1,10 @@
----
-license: mit
-task_categories:
-- token-classification
-language:
-- en
-tags:
-- legal
-size_categories:
-- 1K<n<10K
----
+#Prepare dataset
+```
 python -m venv .venv
 source .venv/bin/activate
-pip install -r requirements.txt
+pip install -r requirements.txt
+```
+#Training
+```
+python hf_model_train.py
+```

adjectives.csv

@@ -0,0 +1,88 @@
+Name
+adaptable
+analytical
+approachable
+articulate
+assertive
+attentive
+collaborative
+communicative
+confident
+conscientious
+creative
+customer-focused
+detail-oriented
+diligent
+dynamic
+efficient
+empathetic
+energetic
+experienced
+flexible
+focused
+goal-oriented
+hardworking
+innovative
+inspiring
+leadership
+motivated
+organized
+passionate
+persistent
+proactive
+professional
+punctual
+reliable
+resourceful
+responsible
+results-driven
+self-motivated
+strategic
+team-oriented
+tech-savvy
+thorough
+trustworthy
+versatile
+visionary
+well-organized
+adroit
+adept
+amiable
+astute
+candid
+capable
+competent
+committed
+conscientious
+considerate
+cordial
+decisive
+dependable
+dynamic
+empathetic
+engaging
+enterprising
+enthusiastic
+forward-thinking
+gracious
+inspirational
+intuitive
+meticulous
+open-minded
+persuasive
+pragmatic
+profound
+reflective
+resourceful
+respectful
+skillful
+steadfast
+stellar
+strategic
+tactful
+thoughtful
+tireless
+unflappable
+visionary
+wise
+zealous

adjectives.py

@@ -0,0 +1,26 @@
+import json
+import logging
+import pathlib
+import pandas as pd
+
+class Adjectives:
+    '''Stores adjectives so you dont have to.'''
+    def __init__(self):
+        self.name = "adjectives"
+        self.logger = logging.getLogger(f"{self.name}")
+        self.logger.setLevel(logging.ERROR)
+        self.file_path = pathlib.Path(__file__).parent.resolve()
+        self.config_file = pathlib.Path(self.file_path) / f"{self.name}.csv"
+        #self.config_file = pathlib.Path(self.file_path) / f"{self.name}.json"
+
+    def get_data(self):
+        dtype={'Name': 'string'}
+        df = pd.read_csv(self.config_file,dtype=dtype)
+        return df['Name']
+        #self.data = self.load_json(self.config_file)
+        #return self.data['data']
+
+    def load_json(self,filename):
+        with open(filename, "r") as f:
+            data = json.load(f)
+        return data

adverbs.csv

@@ -0,0 +1,208 @@
+Name
+accurately
+actively
+adaptively
+adroitly
+appropriately
+clearly
+collaboratively
+consistently
+courteously
+creatively
+diligently
+efficiently
+effectively
+eloquently
+enthusiastically
+flexibly
+graciously
+honestly
+innovatively
+intelligently
+loyally
+methodically
+openly
+precisely
+proactively
+professionally
+promptly
+resourcefully
+responsively
+strategically
+successfully
+swiftly
+thoughtfully
+tirelessly
+transparently
+urgently
+vigorously
+well
+zealously
+ably
+above
+absolutley
+adequately
+afterward
+almost
+always
+anew
+annually
+anxiously
+approximately
+arguably
+awkwardly
+badly
+before
+briefly
+briskly
+carefully
+cautiously
+certainly
+clearly
+closely
+cleverly
+commonly
+consequently
+consistently
+conversely
+daily
+deeply
+deliberately
+diligently
+doubtfully
+dramatically
+early
+eagerly
+efficiently
+elegantly
+energetically
+eventually
+exactly
+exceedingly
+eventually
+exquisitely
+extremely
+frequently
+generally
+gently
+gradually
+greatly
+happily
+hardly
+honestly
+hopelessly
+hourly
+immediately
+impartially
+incessantly
+indeed
+infrequently
+inquisitively
+instantly
+invariably
+jovially
+judiciously
+justly
+kindly
+lately
+lavishly
+lethargically
+likewise
+loudly
+loyally
+madly
+magnificently
+majestically
+merrily
+meticulously
+monthly
+mostly
+mysteriously
+namely
+naturally
+nervously
+never
+normally
+notably
+obliviously
+obviously
+often
+only
+painstakingly
+particularly
+patiently
+perfectly
+periodically
+persistently
+personally
+playfully
+possibly
+precisely
+promptly
+quickly
+quietly
+rapidly
+rarely
+readily
+really
+recently
+regularly
+reluctantly
+repeatedly
+routinely
+sadly
+safely
+scarcely
+seemingly
+seldom
+seriously
+shamelessly
+significantly
+silently
+simply
+sincerely
+smoothly
+so
+solemnly
+sometimes
+soon
+speedily
+steadily
+suddenly
+surely
+systematically
+temporarily
+tenderly
+tensely
+terribly
+thankfully
+thereafter
+tightly
+tomorrow
+too
+totally
+tragically
+truly
+twice
+ultimately
+understandably
+unexpectedly
+unfortunately
+unquestionably
+usually
+utterly
+vastly
+very
+vigorously
+violently
+vividly
+warmly
+weakly
+wearily
+weekly
+well
+willingly
+wonderfully
+yearly
+yesterday
+zealously

adverbs.py

@@ -0,0 +1,26 @@
+import json
+import logging
+import pathlib
+import pandas as pd
+
+class Adverbs:
+    '''Stores adverbs so you dont have to.'''
+    def __init__(self):
+        self.name = "adverbs"
+        self.logger = logging.getLogger(f"{self.name}")
+        self.logger.setLevel(logging.ERROR)
+        self.file_path = pathlib.Path(__file__).parent.resolve()
+        self.config_file = pathlib.Path(self.file_path) / f"{self.name}.csv"
+        #self.config_file = pathlib.Path(self.file_path) / f"{self.name}.json"
+
+    def get_data(self):
+        dtype={'Name': 'string'}
+        df = pd.read_csv(self.config_file,dtype=dtype)
+        return df['Name']
+        #self.data = self.load_json(self.config_file)
+        #return self.data['data']
+
+    def load_json(self,filename):
+        with open(filename, "r") as f:
+            data = json.load(f)
+        return data

alphabetize_dataset.py

@@ -0,0 +1,12 @@
+import pandas as pd
+import traceback
+try:
+    df = pd.read_csv("./2024-01/position_names.csv")
+    df.head()
+    df = df.sort_values(by='Name')
+    df.to_csv("./2024-01/position_names_sorted.csv",index=False)
+except Exception as e:
+    print(e)
+    print(traceback.format_exc())
+
+

conjunctions.csv

@@ -0,0 +1,16 @@
+Name
+and
+as
+because
+but
+for
+however
+if
+moreover
+nevertheless
+or
+so
+therefore
+though
+thus
+yet

conjunctions.py

@@ -0,0 +1,26 @@
+import json
+import logging
+import pathlib
+import pandas as pd
+
+class Conjunctions:
+    '''Stores conjunctions so you dont have to.'''
+    def __init__(self):
+        self.name = "conjunctions"
+        self.logger = logging.getLogger(f"{self.name}")
+        self.logger.setLevel(logging.ERROR)
+        self.file_path = pathlib.Path(__file__).parent.resolve()
+        self.config_file = pathlib.Path(self.file_path) / f"{self.name}.csv"
+        #self.config_file = pathlib.Path(self.file_path) / f"{self.name}.json"
+
+    def get_data(self):
+        dtype={'Name': 'string'}
+        df = pd.read_csv(self.config_file,dtype=dtype)
+        return df['Name']
+        #self.data = self.load_json(self.config_file)
+        #return self.data['data']
+
+    def load_json(self,filename):
+        with open(filename, "r") as f:
+            data = json.load(f)
+        return data

hf_inference.py

@@ -1,9 +1,9 @@
 import pickle
 from transformers import AutoModelForTokenClassification, AutoTokenizer
 from transformers import pipeline
-#text = "A software engineer walked into a library and then took a full stack engineer for coffee."
+text = "A software engineer coded up some software."
 #text="software engineer"
-text="cto"
+#text="cto"
 model = AutoModelForTokenClassification.from_pretrained('./jpn202401')
 tokenizer = AutoTokenizer.from_pretrained(
    './jpn202401', model_max_length=512)

hf_model_train.py

@@ -45,9 +45,9 @@ def compute_metrics(p, label_list):
 
 if __name__ == "__main__":
     model_n_version = "jpn202401"
-    max_epochs = 50
+    max_epochs = 150
     learning_rate = 2e-5
-    batch_size = 16
+    batch_size = 12
     model_root_dir = "."
 
     hf_pretrained_model_checkpoint = "distilbert-base-uncased"

hf_tokenize.py

@@ -63,5 +63,5 @@ if __name__ == '__main__':
 
     tokenized_datasets = dataset.map(hf_preprocessor.tokenize_and_align_labels, batched=True)
 
-    #print("First sample: ", dataset['train'][0])
+    print("First sample: ", dataset['train'][0])
     #print("First tokenized sample: ", tokenized_datasets['train'][0])

make_dataset.py

@@ -1,74 +1,72 @@
+from collections import defaultdict
 import pandas as pd
 import random
-
-def find(token,array):
-    result = False
-    for i,v in enumerate(array):
-        if v.lower().strip() == token.lower().strip():
-            result = True
-            return result
-    return result
+from sentence import SentenceBuilder
 
 file = "./2024-01/position_names.csv"
-predicate_adverbs = ['python','c#','typescript','golang']
-predicate_verbs = ['writes','reads','speaks','presents','talks','tests','checks']
-predicate_nouns = ['code','papers','notebooks','documents','presentations']
-predicate_adjectives = ['.','a','an','and','does','in','not','the','to','yet']
-predicates = []
-predicates.extend(predicate_verbs)
-predicates.extend(predicate_nouns)
-predicates.extend(predicate_adverbs)
-predicates.extend(predicate_adjectives)
-dtype={'Name': 'string'}
+sentence = SentenceBuilder()
+dtype={"Name": "string"}
 df = pd.read_csv(file,dtype=dtype)
-column = df['Name']
+titles = df["Name"]
 tokens = []
-for i,c in enumerate(column):
-    token=""
-    tokenDict={}
-    t=0
-    for j,d in enumerate(c):
-        if t==0 and (d == " " or j==len(c)-1):
-            token += d
-            token = token.strip()
-            if find(token,predicates):
-                #print(token.lower() + 'in')
-                tokenDict['tag'] = 'O'
-            else:
-                #print(token + ' not in')
-                tokenDict['tag'] = 'B-POS'
-            tokenDict['token'] = token
-            tokens.append(tokenDict)
-            token=""
-            tokenDict={}
-            t+=1
-        elif t>0 and (d == " " or j==len(c)-1):
-            token += d
-            token = token.strip()
-            if find(token,predicates):
-                tokenDict['tag'] = 'O'
-            else:
-                tokenDict['tag'] = 'I-POS'
-            tokenDict['token'] = token
-            tokens.append(tokenDict)
-            token=""
-            tokenDict={}
-            t+=1
+for i,t in enumerate(titles):
+    e=0
+    entities=[]
+    entity=""
+    token={}
+    words=[]
+    word=""
+    for j,c in enumerate(t):
+        if e==0 and (c == " " or j==len(t)-1):
+            entity += c
+            entity = entity.strip()
+            entities.append(entity)
+            entity=""
+            e+=1
+            if e==1:
+                words.append(random.choice(sentence.get_adjectives()))
+        elif e>0 and (c == " " or j==len(t)-1):
+            entity += c
+            entity = entity.strip()
+            entities.append(entity)
+            entity=""
+            e+=1
+            if e==2:
+                words.append(random.choice(sentence.get_verbs()))
+            elif e==3:
+                words.append(random.choice(sentence.get_adverbs()))
+            elif e==4:
+                words.append(random.choice(sentence.get_nouns()))
+            elif e==5:
+                words.append(random.choice(sentence.get_conjunctions()))
+            elif e==6:
+                words.append(random.choice(sentence.get_prepositions()))
+            elif e==7:
+                words.append(random.choice(sentence.get_pronouns()))
         else:
-            token += d
-
-tokenDict={}
-num_of_records = 50000
-for _ in range(num_of_records):
-    tokenDict['tag'] = '0'
-    pIndex = random.randint(1,len(predicates)-1)
-    tokenDict['token'] = predicates[pIndex]
-    tokens.append(tokenDict)
-    tokenDict={}
+            entity += c
+    token["entities"] = entities
+    token["words"] = words
+    tokens.append(token)
+    token={}
+    entities=[]
+    words=[]
 
 random.shuffle(tokens)
 
-f = open('./2024-01/position_names_tags.txt', 'w', encoding="utf-8")
-for t in tokens:
-    f.write(t['token'].lower() + " " + t['tag'] + "\n")
-f.close()
+f = open("./2024-01/position_names_tags_new.txt", "w", encoding="utf-8")
+entity_shortname = "POS"
+for i,t in enumerate(tokens):
+    ner_sentence=""
+    ner_tags=""
+    for j,e in enumerate(t["entities"]):
+        ner_sentence += e + " "
+        if j == 0:
+            ner_tags += "B-"+entity_shortname + " "
+        else:
+            ner_tags += "I-"+entity_shortname + " "
+    for k,w in enumerate(t["words"]):
+        ner_sentence += w + " "
+        ner_tags += "O" + " "
+    f.write(ner_sentence + ner_tags + "\n")
+f.close()

nouns.csv

@@ -0,0 +1,307 @@
+Name
+achievement
+analysis
+approach
+budget
+client
+collaboration
+communication
+compliance
+conference
+consultation
+contract
+customer
+data
+deadline
+decision
+delivery
+development
+efficiency
+employee
+engagement
+evaluation
+execution
+expense
+feedback
+goal
+innovation
+integration
+leadership
+management
+meeting
+negotiation
+objective
+operation
+opportunity
+organization
+performance
+plan
+policy
+presentation
+problem
+productivity
+project
+proposal
+quality
+report
+research
+revenue
+risk
+sales
+solution
+strategy
+success
+team
+technology
+training
+value
+vision
+workshop
+analysis
+application
+assessment
+audit
+benchmark
+brand
+business
+campaign
+case
+change
+clientele
+communication
+compensation
+competency
+conference
+consultation
+consumer
+contract
+contribution
+convention
+cooperation
+corporate
+culture
+customer
+data
+deadline
+decision
+delivery
+dependability
+development
+documentation
+economy
+efficiency
+employee
+employment
+engagement
+enterprise
+evaluation
+execution
+expectation
+experience
+experiment
+expense
+experiment
+facilitation
+feedback
+finance
+forecast
+fulfillment
+goal
+growth
+guidance
+implementation
+improvement
+incentive
+income
+innovation
+integration
+investment
+issue
+job
+knowledge
+leadership
+learning
+loyalty
+management
+market
+meeting
+negotiation
+objective
+operationalization
+opportunity
+organization
+outcomes
+partnership
+performance
+plan
+policy
+portfolio
+position
+possibility
+potential
+preparation
+presentation
+problem
+procedure
+process
+product
+profit
+program
+project
+proposal
+quality
+recruitment
+reputation
+research
+resolution
+responsibility
+revenue
+risk
+sales
+satisfaction
+schedule
+service
+solution
+staff
+standardization
+strategy
+success
+sustainability
+system
+task
+team
+technology
+time
+training
+transformation
+understanding
+value
+vision
+wealth
+work
+workplace
+workshop
+analysis
+approach
+assessment
+audit
+benchmark
+brand
+business
+campaign
+case
+change
+clientele
+communication
+compensation
+competency
+conference
+consultation
+consumer
+contract
+contribution
+convention
+cooperation
+corporate
+culture
+customer
+data
+deadline
+decision
+delivery
+dependability
+development
+documentation
+economy
+efficiency
+employee
+employment
+engagement
+enterprise
+evaluation
+execution
+expectation
+experience
+experiment
+expense
+experiment
+facilitation
+feedback
+finance
+forecast
+fulfillment
+goal
+growth
+guidance
+implementation
+improvement
+incentive
+income
+innovation
+integration
+investment
+issue
+job
+knowledge
+leadership
+learning
+loyalty
+management
+market
+meeting
+negotiation
+objective
+operationalization
+opportunity
+organization
+outcomes
+partnership
+performance
+plan
+policy
+portfolio
+position
+possibility
+potential
+preparation
+presentation
+problem
+procedure
+process
+product
+profit
+program
+project
+proposal
+quality
+recruitment
+reputation
+research
+resolution
+responsibility
+revenue
+risk
+sales
+satisfaction
+schedule
+service
+solution
+staff
+standardization
+strategy
+success
+sustainability
+system
+task
+team
+technology
+time
+training
+transformation
+understanding
+value
+vision
+wealth
+work
+workplace
+workshop

nouns.json

@@ -0,0 +1,310 @@
+{
+  "data": [
+  {"name": "Achievement"},
+  {"name": "Analysis"},
+  {"name": "Approach"},
+  {"name": "Budget"},
+  {"name": "Client"},
+  {"name": "Collaboration"},
+  {"name": "Communication"},
+  {"name": "Compliance"},
+  {"name": "Conference"},
+  {"name": "Consultation"},
+  {"name": "Contract"},
+  {"name": "Customer"},
+  {"name": "Data"},
+  {"name": "Deadline"},
+  {"name": "Decision"},
+  {"name": "Delivery"},
+  {"name": "Development"},
+  {"name": "Efficiency"},
+  {"name": "Employee"},
+  {"name": "Engagement"},
+  {"name": "Evaluation"},
+  {"name": "Execution"},
+  {"name": "Expense"},
+  {"name": "Feedback"},
+  {"name": "Goal"},
+  {"name": "Innovation"},
+  {"name": "Integration"},
+  {"name": "Leadership"},
+  {"name": "Management"},
+  {"name": "Meeting"},
+  {"name": "Negotiation"},
+  {"name": "Objective"},
+  {"name": "Operation"},
+  {"name": "Opportunity"},
+  {"name": "Organization"},
+  {"name": "Performance"},
+  {"name": "Plan"},
+  {"name": "Policy"},
+  {"name": "Presentation"},
+  {"name": "Problem"},
+  {"name": "Productivity"},
+  {"name": "Project"},
+  {"name": "Proposal"},
+  {"name": "Quality"},
+  {"name": "Report"},
+  {"name": "Research"},
+  {"name": "Revenue"},
+  {"name": "Risk"},
+  {"name": "Sales"},
+  {"name": "Solution"},
+  {"name": "Strategy"},
+  {"name": "Success"},
+  {"name": "Team"},
+  {"name": "Technology"},
+  {"name": "Training"},
+  {"name": "Value"},
+  {"name": "Vision"},
+  {"name": "Workshop"},
+  {"name": "Analysis"},
+  {"name": "Application"},
+  {"name": "Assessment"},
+  {"name": "Audit"},
+  {"name": "Benchmark"},
+  {"name": "Brand"},
+  {"name": "Business"},
+  {"name": "Campaign"},
+  {"name": "Case"},
+  {"name": "Change"},
+  {"name": "Clientele"},
+  {"name": "Communication"},
+  {"name": "Compensation"},
+  {"name": "Competency"},
+  {"name": "Conference"},
+  {"name": "Consultation"},
+  {"name": "Consumer"},
+  {"name": "Contract"},
+  {"name": "Contribution"},
+  {"name": "Convention"},
+  {"name": "Cooperation"},
+  {"name": "Corporate"},
+  {"name": "Culture"},
+  {"name": "Customer"},
+  {"name": "Data"},
+  {"name": "Deadline"},
+  {"name": "Decision"},
+  {"name": "Delivery"},
+  {"name": "Dependability"},
+  {"name": "Development"},
+  {"name": "Documentation"},
+  {"name": "Economy"},
+  {"name": "Efficiency"},
+  {"name": "Employee"},
+  {"name": "Employment"},
+  {"name": "Engagement"},
+  {"name": "Enterprise"},
+  {"name": "Evaluation"},
+  {"name": "Execution"},
+  {"name": "Expectation"},
+  {"name": "Experience"},
+  {"name": "Experiment"},
+  {"name": "Expense"},
+  {"name": "Experiment"},
+  {"name": "Facilitation"},
+  {"name": "Feedback"},
+  {"name": "Finance"},
+  {"name": "Forecast"},
+  {"name": "Fulfillment"},
+  {"name": "Goal"},
+  {"name": "Growth"},
+  {"name": "Guidance"},
+  {"name": "Implementation"},
+  {"name": "Improvement"},
+  {"name": "Incentive"},
+  {"name": "Income"},
+  {"name": "Innovation"},
+  {"name": "Integration"},
+  {"name": "Investment"},
+  {"name": "Issue"},
+  {"name": "Job"},
+  {"name": "Knowledge"},
+  {"name": "Leadership"},
+  {"name": "Learning"},
+  {"name": "Loyalty"},
+  {"name": "Management"},
+  {"name": "Market"},
+  {"name": "Meeting"},
+  {"name": "Negotiation"},
+  {"name": "Objective"},
+  {"name": "Operationalization"},
+  {"name": "Opportunity"},
+  {"name": "Organization"},
+  {"name": "Outcomes"},
+  {"name": "Partnership"},
+  {"name": "Performance"},
+  {"name": "Plan"},
+  {"name": "Policy"},
+  {"name": "Portfolio"},
+  {"name": "Position"},
+  {"name": "Possibility"},
+  {"name": "Potential"},
+  {"name": "Preparation"},
+  {"name": "Presentation"},
+  {"name": "Problem"},
+  {"name": "Procedure"},
+  {"name": "Process"},
+  {"name": "Product"},
+  {"name": "Profit"},
+  {"name": "Program"},
+  {"name": "Project"},
+  {"name": "Proposal"},
+  {"name": "Quality"},
+  {"name": "Recruitment"},
+  {"name": "Reputation"},
+  {"name": "Research"},
+  {"name": "Resolution"},
+  {"name": "Responsibility"},
+  {"name": "Revenue"},
+  {"name": "Risk"},
+  {"name": "Sales"},
+  {"name": "Satisfaction"},
+  {"name": "Schedule"},
+  {"name": "Service"},
+  {"name": "Solution"},
+  {"name": "Staff"},
+  {"name": "Standardization"},
+  {"name": "Strategy"},
+  {"name": "Success"},
+  {"name": "Sustainability"},
+  {"name": "System"},
+  {"name": "Task"},
+  {"name": "Team"},
+  {"name": "Technology"},
+  {"name": "Time"},
+  {"name": "Training"},
+  {"name": "Transformation"},
+  {"name": "Understanding"},
+  {"name": "Value"},
+  {"name": "Vision"},
+  {"name": "Wealth"},
+  {"name": "Work"},
+  {"name": "Workplace"},
+  {"name": "Workshop"},
+  {"name": "Analysis"},
+  {"name": "Approach"},
+  {"name": "Assessment"},
+  {"name": "Audit"},
+  {"name": "Benchmark"},
+  {"name": "Brand"},
+  {"name": "Business"},
+  {"name": "Campaign"},
+  {"name": "Case"},
+  {"name": "Change"},
+  {"name": "Clientele"},
+  {"name": "Communication"},
+  {"name": "Compensation"},
+  {"name": "Competency"},
+  {"name": "Conference"},
+  {"name": "Consultation"},
+  {"name": "Consumer"},
+  {"name": "Contract"},
+  {"name": "Contribution"},
+  {"name": "Convention"},
+  {"name": "Cooperation"},
+  {"name": "Corporate"},
+  {"name": "Culture"},
+  {"name": "Customer"},
+  {"name": "Data"},
+  {"name": "Deadline"},
+  {"name": "Decision"},
+  {"name": "Delivery"},
+  {"name": "Dependability"},
+  {"name": "Development"},
+  {"name": "Documentation"},
+  {"name": "Economy"},
+  {"name": "Efficiency"},
+  {"name": "Employee"},
+  {"name": "Employment"},
+  {"name": "Engagement"},
+  {"name": "Enterprise"},
+  {"name": "Evaluation"},
+  {"name": "Execution"},
+  {"name": "Expectation"},
+  {"name": "Experience"},
+  {"name": "Experiment"},
+  {"name": "Expense"},
+  {"name": "Experiment"},
+  {"name": "Facilitation"},
+  {"name": "Feedback"},
+  {"name": "Finance"},
+  {"name": "Forecast"},
+  {"name": "Fulfillment"},
+  {"name": "Goal"},
+  {"name": "Growth"},
+  {"name": "Guidance"},
+  {"name": "Implementation"},
+  {"name": "Improvement"},
+  {"name": "Incentive"},
+  {"name": "Income"},
+  {"name": "Innovation"},
+  {"name": "Integration"},
+  {"name": "Investment"},
+  {"name": "Issue"},
+  {"name": "Job"},
+  {"name": "Knowledge"},
+  {"name": "Leadership"},
+  {"name": "Learning"},
+  {"name": "Loyalty"},
+  {"name": "Management"},
+  {"name": "Market"},
+  {"name": "Meeting"},
+  {"name": "Negotiation"},
+  {"name": "Objective"},
+  {"name": "Operationalization"},
+  {"name": "Opportunity"},
+  {"name": "Organization"},
+  {"name": "Outcomes"},
+  {"name": "Partnership"},
+  {"name": "Performance"},
+  {"name": "Plan"},
+  {"name": "Policy"},
+  {"name": "Portfolio"},
+  {"name": "Position"},
+  {"name": "Possibility"},
+  {"name": "Potential"},
+  {"name": "Preparation"},
+  {"name": "Presentation"},
+  {"name": "Problem"},
+  {"name": "Procedure"},
+  {"name": "Process"},
+  {"name": "Product"},
+  {"name": "Profit"},
+  {"name": "Program"},
+  {"name": "Project"},
+  {"name": "Proposal"},
+  {"name": "Quality"},
+  {"name": "Recruitment"},
+  {"name": "Reputation"},
+  {"name": "Research"},
+  {"name": "Resolution"},
+  {"name": "Responsibility"},
+  {"name": "Revenue"},
+  {"name": "Risk"},
+  {"name": "Sales"},
+  {"name": "Satisfaction"},
+  {"name": "Schedule"},
+  {"name": "Service"},
+  {"name": "Solution"},
+  {"name": "Staff"},
+  {"name": "Standardization"},
+  {"name": "Strategy"},
+  {"name": "Success"},
+  {"name": "Sustainability"},
+  {"name": "System"},
+  {"name": "Task"},
+  {"name": "Team"},
+  {"name": "Technology"},
+  {"name": "Time"},
+  {"name": "Training"},
+  {"name": "Transformation"},
+  {"name": "Understanding"},
+  {"name": "Value"},
+  {"name": "Vision"},
+  {"name": "Wealth"},
+  {"name": "Work"},
+  {"name": "Workplace"},
+  {"name": "Workshop"}
+  ]
+}

nouns.py

@@ -0,0 +1,26 @@
+import json
+import logging
+import pathlib
+import pandas as pd
+
+class Nouns:
+    '''Stores Nouns so you dont have to.'''
+    def __init__(self):
+        self.name = "nouns"
+        self.logger = logging.getLogger(f"{self.name}")
+        self.logger.setLevel(logging.ERROR)
+        self.file_path = pathlib.Path(__file__).parent.resolve()
+        self.config_file = pathlib.Path(self.file_path) / f"{self.name}.csv"
+        #self.config_file = pathlib.Path(self.file_path) / f"{self.name}.json"
+
+    def get_data(self):
+        dtype={'Name': 'string'}
+        df = pd.read_csv(self.config_file,dtype=dtype)
+        return df['Name']
+        #self.data = self.load_json(self.config_file)
+        #return self.data['data']
+
+    def load_json(self,filename):
+        with open(filename, "r") as f:
+            data = json.load(f)
+        return data

prepositions.csv

@@ -0,0 +1,57 @@
+Name
+about
+above
+across
+after
+against
+along
+amid
+among
+around
+as
+at
+before
+behind
+below
+beneath
+beside
+between
+beyond
+by
+concerning
+considering
+despite
+down
+during
+except
+for
+from
+in
+inside
+into
+like
+near
+of
+off
+on
+onto
+out
+outside
+over
+past
+regarding
+round
+since
+through
+throughout
+to
+toward
+under
+underneath
+until
+unto
+up
+upon
+with
+within
+without

prepositions.py

@@ -0,0 +1,26 @@
+import json
+import logging
+import pathlib
+import pandas as pd
+
+class Prepositions:
+    '''Stores prepostions so you dont have to.'''
+    def __init__(self):
+        self.name = "prepositions"
+        self.logger = logging.getLogger(f"{self.name}")
+        self.logger.setLevel(logging.ERROR)
+        self.file_path = pathlib.Path(__file__).parent.resolve()
+        self.config_file = pathlib.Path(self.file_path) / f"{self.name}.csv"
+        #self.config_file = pathlib.Path(self.file_path) / f"{self.name}.json"
+
+    def get_data(self):
+        dtype={'Name': 'string'}
+        df = pd.read_csv(self.config_file,dtype=dtype)
+        return df['Name']
+        #self.data = self.load_json(self.config_file)
+        #return self.data['data']
+
+    def load_json(self,filename):
+        with open(filename, "r") as f:
+            data = json.load(f)
+        return data

pronouns.csv

@@ -0,0 +1,63 @@
+Name
+i
+you
+he
+she
+it
+we
+they
+me
+you
+him
+her
+us
+them
+myself
+yourself
+himself
+herself
+itself
+ourselves
+themselves
+mine
+yours
+his
+hers
+its
+ours
+theirs
+this
+that
+these
+those
+some
+any
+all
+none
+each
+every
+either
+neither
+both
+few
+many
+several
+one
+someone
+somebody
+something
+anyone
+anybody
+anything
+everyone
+everybody
+everything
+no one
+nobody
+nothing
+another
+other
+others
+another
+each other
+one another

pronouns.py

@@ -0,0 +1,26 @@
+import json
+import logging
+import pathlib
+import pandas as pd
+
+class Pronouns:
+    '''Stores pronouns so you dont have to.'''
+    def __init__(self):
+        self.name = "pronouns"
+        self.logger = logging.getLogger(f"{self.name}")
+        self.logger.setLevel(logging.ERROR)
+        self.file_path = pathlib.Path(__file__).parent.resolve()
+        self.config_file = pathlib.Path(self.file_path) / f"{self.name}.csv"
+        #self.config_file = pathlib.Path(self.file_path) / f"{self.name}.json"
+
+    def get_data(self):
+        dtype={'Name': 'string'}
+        df = pd.read_csv(self.config_file,dtype=dtype)
+        return df['Name']
+        #self.data = self.load_json(self.config_file)
+        #return self.data['data']
+
+    def load_json(self,filename):
+        with open(filename, "r") as f:
+            data = json.load(f)
+        return data

sentence.py

@@ -0,0 +1,38 @@
+from adjectives import Adjectives
+from adverbs import Adverbs
+from conjunctions import Conjunctions
+from nouns import Nouns
+from prepositions import Prepositions
+from pronouns import Pronouns
+from verbs import Verbs
+
+class SentenceBuilder:
+    def __init__(self):
+        self.adjectives = Adjectives()
+        self.adverbs = Adverbs()
+        self.conjunctions = Conjunctions()
+        self.nouns = Nouns()
+        self.prepositions = Prepositions()
+        self.pronouns = Pronouns()
+        self.verbs = Verbs()
+
+    def get_adjectives(self):
+        return self.adjectives.get_data()
+
+    def get_adverbs(self):
+        return self.adverbs.get_data()
+    
+    def get_conjunctions(self):
+        return self.conjunctions.get_data()
+    
+    def get_nouns(self):
+        return self.nouns.get_data()
+    
+    def get_prepositions(self):
+        return self.prepositions.get_data()
+    
+    def get_pronouns(self):
+        return self.pronouns.get_data()
+    
+    def get_verbs(self):
+        return self.verbs.get_data()

split_dataset.py

@@ -1,22 +1,16 @@
 import traceback
 try:
-    validate_max=33000
-    train_max=80000
-    fp = open("./2024-01/position_names_tags.txt",'r')
+    train_max=400
+    t = open("./2024-01/position_names_tags.txt",'r')
     train = open("./2024-01/train.txt","w")
-    validate = open("./2024-01/validate.txt","w")
     test = open("./2024-01/test.txt","w")
-    for i,l in enumerate(fp):
-        print(i,l)
-        if i <= validate_max:
-            validate.write(l)
-        elif i > validate_max and i <= train_max:
+    for i,l in enumerate(t):
+        if i <= train_max:
             train.write(l)
         else:
             test.write(l)
-    fp.close()
+    t.close()
     train.close()
-    validate.close()
     test.close()
 
 except Exception as e:

verbs.csv

@@ -0,0 +1,40 @@
+Name
+achieve
+analyze
+checks
+codes
+communicate
+collaborate
+coordinate
+demonstrate
+develop
+direct
+evaluate
+execute
+facilitate
+generate
+implement
+influence
+lead
+manage
+negotiate
+organize
+plan
+presents
+prioritize
+problem-solve
+programs
+project-manage
+reads
+recommend
+research
+speaks
+streamline
+supervise
+synthesize
+talks
+tests
+train
+transform
+utilize
+writes

verbs.py

@@ -0,0 +1,26 @@
+import json
+import logging
+import pathlib
+import pandas as pd
+
+class Verbs:
+    '''Stores verbs so you dont have to.'''
+    def __init__(self):
+        self.name = "verbs"
+        self.logger = logging.getLogger(f"{self.name}")
+        self.logger.setLevel(logging.ERROR)
+        self.file_path = pathlib.Path(__file__).parent.resolve()
+        self.config_file = pathlib.Path(self.file_path) / f"{self.name}.csv"
+        #self.config_file = pathlib.Path(self.file_path) / f"{self.name}.json"
+
+    def get_data(self):
+        dtype={'Name': 'string'}
+        df = pd.read_csv(self.config_file,dtype=dtype)
+        return df['Name']
+        #self.data = self.load_json(self.config_file)
+        #return self.data['data']
+
+    def load_json(self,filename):
+        with open(filename, "r") as f:
+            data = json.load(f)
+        return data