Model Core Primitives - Author: Wang Jiaocheng#
Language Understanding Primitives (38 items)#
- Token Locator: Converts text into a sequence of morphemes (handles Chinese without spaces / English roots)
- Subword Segmenter: Processes out-of-vocabulary words (e.g., "ChatGPT"→["Chat","G","PT"])
- Dependency Parser: Constructs subject-verb-object syntax trees
- Phrase Structure Analyzer: Identifies noun phrase/verb phrase boundaries
- Syntactic Role Tagger: Tags subject, predicate, object, modifiers, and complements
- Entity Recognizer: Identifies person names, place names, and organization names
- Anaphora Resolver: Resolves what "it"/"they" refers to
- Semantic Role Tagger: Tags agent, patient, time, and location
- Concept Linker: Links words to knowledge graph nodes
- Dialogue State Tracker: Maintains focus in multi-turn conversations
- Coreference Chain Builder: Relates the same entity across sentences
- Implicit Reasoner: Fills in logical gaps (e.g., "It's raining"→"Need to bring an umbrella")
- Action Classifier: Identifies requests, statements, questions, and commands
- Sentiment Polarity Detector: Quantifies positive and negative emotions
- Context-Aware Fusion Engine: Integrates multi-source contextual information
- Ambiguity Resolver: Addresses polysemy issues (e.g., "apple"→fruit/company)
- Temporal Anchor: Converts relative time to absolute time (e.g., "next week"→specific date)
- Metaphor Parser: Understands the true meaning of metaphorical expressions
- Irony Detector: Identifies ironic intentions in discourse
- Fuzzy Modifier Parser: Handles uncertain expressions like "probably"/"possibly"
- Topic Boundary Detector: Determines points of topic shifts in conversation
- Intent Priority Evaluator: Ranks the importance of multiple requests
- Multilingual Aligner: Handles mixed language input
- Spoken Feature Processor: Adapts to incomplete expressions in spoken language
- Document Structure Parser: Identifies formatting information like titles, paragraphs, and lists
- Format Error Corrector: Automatically fixes spelling and grammar errors
- Domain Terminology Recognizer: Locates specialized vocabulary in professional fields
- Dialect Adapter: Understands language variants from different regions
- Cultural Reference Parser: Handles expressions with specific cultural backgrounds
- Emotion Intensity Quantifier: Assesses the degree of joy, anger, sadness, and happiness
- Speech-to-Text Post-Processor: Optimizes the text quality of ASR output
- Non-Verbal Symbol Interpreter: Understands the implied meanings of emojis and punctuation
- Implicit Premise Detector: Reveals unspoken assumptions
- Negation Scope Analyzer: Determines the scope of negation
- Question Type Classifier: Distinguishes between yes/no questions and special inquiries
- Command Strength Evaluator: Quantifies the degree of forcefulness in instructions
- Stylistic Style Recognizer: Analyzes formal, casual, poetic, and other styles
- Cross-Modal Aligner: Coordinates the correspondence between text and images/speech
Knowledge Operation Primitives (29 items)#
- Knowledge Retriever: Extracts facts from 175 billion parameters
- Relation Reasoner: Infers implicit relationships (A is B's teacher → B is A's student)
- Attribute Filler: Completes object attributes (known capital → look up population)
- Temporal Reasoner: Handles temporal relationships (e.g., "last March"→2023-03)
- Spatial Reasoner: Handles positional relationships (e.g., "A is north of B"→coordinate calculation)
- Numerical Estimator: Handles vague numbers (e.g., "many"→probability distribution)
- Concept Classifier: Constructs classification trees (apple→fruit→plant)
- Counterfactual Simulator: Handles hypothetical scenarios (e.g., "if electricity had not been invented")
- Knowledge Conflict Resolver: Resolves contradictory information (conflicting data from different sources)
- Ontology Mapper: Connects concepts from different knowledge systems
- Common Sense Reasoner: Logical inference based on everyday experiences
- Event Chain Builder: Establishes causal and temporal relationship networks
- Analogy Engine: Transfers knowledge between similar scenarios
- Knowledge Completeness Checker: Identifies information gaps
- Cross-Domain Transferrer: Applies knowledge from domain A to solve problems in domain B
- Probability Fact Updater: Adjusts belief levels based on new evidence
- Complex System Modeler: Analyzes interactions among multiple factors
- Constraint Propagator: Infers constraints within rule networks
- Pattern Expander: Derives general rules from specific cases
- Knowledge Fusion Engine: Merges information from multiple sources
- Concept Refinement Tool: Transforms vague descriptions into precise definitions
- Cognitive Bias Detector: Identifies unreasonable premises
- Knowledge Reliability Evaluator: Assigns weights to different sources
- Trend Extrapolator: Predicts the future based on historical data
- Scenario Simulator: Constructs complete event scenarios
- Abstraction Level Selector: Dynamically adjusts knowledge granularity
- Knowledge Distiller: Extracts core information from complex data
- Multimodal Knowledge Integrator: Coordinates representations of text, images, and data
- Knowledge Version Tracker: Records the timeliness of information
Language Generation Primitives (32 items)#
- Information Selector: Filters relevant knowledge points
- Structure Planner: Determines overall and sub-structure (problem-solution, etc.)
- Anaphora Expression Optimizer: Avoids repetitive nouns (using pronouns/synonyms)
- Connector Word Selector: Accurately uses conjunctions like because, but, and, etc.
- Tense Consistency Engine: Maintains tense uniformity throughout the text
- Quantity Expression Optimizer: Handles singular/plural and quantifiers (e.g., "three apples")
- Formality Regulator: Controls the degree of spoken vs. written language
- Domain Terminology Adapter: Switches between medical, legal, and technical terminology
- Cultural Sensitivity Filter: Avoids culturally taboo expressions
- Logical Validator: Checks the rationality of causal relationships
- Fact Consistency Checker: Ensures generation aligns with the knowledge base
- Emotion Infuser: Injects appropriate emotional tones
- Audience Adapter: Adjusts expressions based on user background
- Rhetorical Optimizer: Enhances the expressiveness of communication
- Redundancy Eliminator: Removes unnecessary repetitions
- Ambiguity Preventer: Avoids potentially misleading expressions
- Information Density Controller: Balances detail and conciseness
- Dialogue Strategy Selector: Decides on providing, asking, or guiding strategies
- Multilingual Generator: Simultaneously processes outputs in multiple languages
- Multimedia Coordinator: Generates image descriptions alongside text
- Error Recovery Generator: Handles graceful responses to unknown queries
- Explanation Depth Selector: Dynamically adjusts the detail of explanations
- Counterfactual Describer: Accurately describes hypothetical scenarios
- Stance Expressor: Appropriately expresses support or opposition
- Vagueness Controller: Handles expressions of uncertainty
- Meta-Communication Generator: Explains its own thought processes
- Ethical Trade-off Describer: Shows the pros and cons of different choices
- Format Normalizer: Adapts paragraphs, lists, titles, and other formatting
- Context Connector: Links the current conversation with previous ones
- Instant Corrector: Dynamically optimizes the content being generated
- Safety Boundary Controller: Avoids expressions that suggest dangerous advice
- Generation Diversity Selector: Adjusts the level of creative expression
Reasoning and Decision-Making Primitives (18 items)#
- Rule Engine: Executes hard rules using if-then-else logic
- Analogy Reasoner: A :: C:? pattern matching
- Probability Reasoner: Calculates the probability distribution of multiple options
- Optimization Selector: Multi-objective weight decision-making (speed vs. accuracy)
- Abductive Reasoner: Infers causes from phenomena
- Causal Graph Builder: Constructs causal relationship networks among variables
- Constraint Solver: Solves problems with constraints (e.g., scheduling)
- Ethical Trade-off Framework: Evaluates the ethical implications of decisions
- Cost-Benefit Analyzer: Quantifies the value-cost ratio of decisions
- Risk Predictor: Assesses potential adverse outcomes of decisions
- Alternative Solution Generator: Creates Plan B options
- Counter-Evidence Engine: Seeks evidence against hypotheses
- Systems Thinking Model: Considers second-order and third-order effects
- Bias Detector: Identifies subjective tendencies in decision-making
- Time Sensitivity Evaluator: Balances response speed and quality
- Resource Optimizer: Allocates computational resources efficiently
- Knowledge Gap Identifier: Recognizes information gaps that need to be avoided
- Feasibility Evaluator: Checks the operational feasibility of plans
Meta-Management Primitives (System-Level 18 items)#
- Attention Focus Enhancer: Increases the weight of key areas
- Attention Suppressor: Reduces the weight of noisy areas
- Harmful Content Detector: Identifies violent, biased, or illegal content
- Hallucination Suppressor: Lowers the probability of fabricating facts
- Computational Budget Allocator: Dynamically allocates GPU memory
- Early Termination Predictor: Ends low-confidence branches early
- Decision Attribution Analyzer: Marks key input words that influence output
- Confidence Calibrator: Quantifies the reliability score of outputs
- Contradiction Monitor: Detects logical conflicts between input and output
- Knowledge Timeliness Validator: Checks the recency of information
- Thought Chain Optimizer: Balances reasoning depth and efficiency
- Fairness Auditor: Checks for processing differences among different groups
- Transparency Controller: Manages the level of detail exposed in explanations
- Resource Reclaimer: Timely releases inactive memory
- Capability Boundary Marker: Identifies situations that exceed knowledge boundaries
- Robustness Enhancer: Handles noisy inputs
- Version Coordinator: Ensures compatibility of behavior after updates
- Performance-Quality Trade-off Controller: Dynamically balances response speed and accuracy