Mixed Deck — All NLP Topics Flashcards
100 cards from real NLP practice questions. Tap to flip, then mark Knew It or Still Learning — missed cards come back until you master them.
Read the first 20 Mixed Deck — All NLP Topics flashcards as text
The NLP principle that 'the map is not the territory' is most relevant to reframing because:
Answer: It reminds us that a client's problem is their interpretation, not objective reality
Reframing works precisely because the client's map (interpretation) can be changed even when the external event (territory) cannot.
In NLP calibration, what does a client's sudden shift to shallow breathing typically signal?
Answer: Emotional discomfort or stress
Shallow breathing is a physiological cue often associated with tension or discomfort, which a calibrated NLP coach learns to detect and address.
What is 'detokenization' in NLP?
Answer: Converting a sequence of tokens back into a human-readable string
Detokenization reconstructs the original (or near-original) text string from a list of tokens, reversing the tokenization process.
What is the primary function of a softmax layer at the output of a text classification neural network?
Answer: To convert raw logits into a probability distribution over all classes
Softmax exponentiates each logit and divides by the sum, producing a valid probability distribution where all class probabilities sum to 1.
What is 'subjectivity detection' as a preprocessing step in sentiment analysis?
Answer: Distinguishing objective factual statements from subjective opinionated text
Subjectivity detection filters out objective sentences so sentiment analysis focuses only on opinion-bearing content.
The 'Belief Audit' in NLP coaching involves:
Answer: Systematically identifying both empowering and limiting beliefs relevant to a client's goal
A belief audit maps the client's current belief landscape—both supportive and restrictive beliefs—as a foundation for targeted change work.
Which of the following best describes the 'bag-of-words' representation after text preprocessing?
Answer: An unordered collection of word frequencies ignoring grammar
Bag-of-words represents text as an unordered set of word counts, discarding grammar and word order information.
What is the most important professional competency for NLP certification in named entity recognition?
Answer: Deep knowledge combined with practical application skills
Professional competency requires both deep knowledge of the subject matter and the ability to apply that knowledge in practical situations.
What is the role of 'Layer Normalization' in a Transformer language model?
Answer: It stabilizes training by normalizing activations across the feature dimension within each layer
Layer normalization standardizes activations within each layer to zero mean and unit variance, stabilizing training and allowing higher learning rates.
Why might a tokenizer produce different numbers of tokens for the same English word depending on whether it appears at the start of a sentence or mid-sentence in GPT-style BPE?
Answer: GPT-style BPE treats a leading space as part of the token, so 'dog' and ' dog' are different tokens
GPT tokenizers prepend a space to most words as a prefix (e.g., 'Ġdog'), distinguishing a word at the start of a sentence from a mid-sentence occurrence.
Which of the following is a key risk when an NLP coach incorrectly labels a client's meta-program based on one context?
Answer: The coach may design interventions mismatched to the client's actual natural patterns
Meta-programs are context-dependent and misidentifying them based on one situation can lead to coaching strategies that are ineffective or counterproductive.
How does the NLP body of knowledge relate to daily professional practice?
Answer: It provides the foundational framework that guides decision-making and standard practices
The body of knowledge provides the foundational framework of principles, standards, and best practices that professionals use to guide their daily decision-making, ensure consistent quality, and maintain alignment with industry standards.
In NLP practice, what is the best approach to quality improvement in word embeddings?
Answer: Use data-driven methods with measurable outcomes
Data-driven quality improvement with measurable outcomes ensures that changes actually produce the intended improvements and can be verified.
Which of the following best describes the 'O' label in BIO tagging?
Answer: A token that belongs to no named entity
In BIO tagging, O (Outside) marks tokens that are not part of any named entity, forming the majority class in most NER datasets.
What is a 'mixture of experts' (MoE) architecture in the context of large language models?
Answer: A model architecture where each input token is routed to only a subset of specialized sub-networks (experts) rather than all parameters
In MoE models, a learned gating network routes each token to a sparse subset of 'expert' feed-forward layers, enabling very large total parameter counts without proportionally increasing compute.
What distinguishes 'conscious rapport' from 'unconscious rapport' in NLP?
Answer: Conscious rapport involves intentional mirroring while unconscious rapport arises naturally
Conscious rapport involves the deliberate application of mirroring and pacing techniques, while unconscious rapport emerges naturally in genuine connection.
A 'core transformation' in NLP, as developed by Connirae Andreas, aims to:
Answer: Replace surface behaviors by discovering and fulfilling the deepest core state behind them
Core Transformation works through a parts negotiation to uncover the deepest positive intention—often a state like peace or wholeness—and fulfill it directly, transforming the part and its behavior.
In transformer-based NER, why is subword tokenization (e.g., WordPiece) potentially problematic?
Answer: Entity boundaries may fall within a subword split, complicating label alignment
Subword tokenization can split a single word into multiple tokens, requiring strategies to align word-level NER labels with subword tokens.
Which of the following is not a foundational component of NLP? (NLP)
Answer: None of the above
Flexibility (if what you are doing is not working, then do something else), Outcome (knowing what you want), and Feedback (how will you know you are getting what you want?) are all foundational components of NLP, often referred to as the 'NLP Success Formula.' They are essential for achieving desired results and effective change.
Determine the sensory input channels in the Neuro-linguistic programming (NLP) communication model that include the ability of people to distinguish between distinct flavors.
Answer: Gustatory
The gustatory sensory input channel specifically refers to the sense of taste, enabling individuals to distinguish between various flavors. While often grouped with kinesthetic, gustatory is a distinct representational system in NLP, focusing on taste experiences and how they contribute to our perception of reality.