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Natural Language Processing

A language-system record follows the exact construction of model context: what arrived, what was retained or retrieved, in what order it was assembled, and which rule changed the generated result or the next system action.

tokens / promptretrieved contextresponse

Interaction

External sequence

  • turn
  • message
  • session
  • audio input

Representation

Language objects

  • token
  • embedding
  • context window
  • retrieval result

Model

Transformation

  • attention
  • retrieval
  • generation
  • classification

Control

Operational boundary

  • policy
  • evaluation
  • scheduler
  • fallback
ObjectStructureRecordForm
Agent systemApplication, orchestrator, specialist services, model servicesService boundary, call order, data passedSystem architecture
Conversation flowTurns, state, memory, request and responseTurn trigger, retained context, state transitionSequence / state map
Model architectureEncoder, attention or speech network, output headLayer function, input representation, output representationLayered model
Prompt and contextInstruction, retrieved context, user input, qualifiersAssembly order, source, editing or filtering operationContext assembly map
Retrieval-augmented generationRetriever, source, result object, generator, feedbackRetrieval criterion, result fields, augmentation and generation linkRetrieve → augment → generate
Policy and guardrailInput, policy test, branch, actionDecision condition, permitted or altered output, fallbackPolicy decision tree
Training and fine-tuningTraining data, preparation, objective, reward or loss, validationData lineage, update mechanism, evaluation protocolTraining flow
EvaluationMetric, threshold, comparison, resulting actionMetric definition, benchmark set, decision consequenceEvaluation loop
Inference servingRequest, scheduler, model instance, cache or resource poolAllocation, timing, state, scale behaviorService timeline
Text and audio objectsToken, embedding, memory, index, acoustic feature, waveformObject fields, conversions, producer and consumerData schema / signal chain

request → state → response

Turn record

The state retained between interactions and the operation applied in each turn.

source + order + window

Context record

Where context came from and how it entered the model input.

fragment + score + source

Retrieval object

Fields carried from retrieval into generation or evaluation.

metric → threshold → action

Evaluation record

A defined measure and the system behavior that follows from it.

Turn

A request arrives with an identified session state and retained context.

Retrieve

A query reaches an index and returns ranked result objects with source and score fields.

Assemble

Instructions, retrieved fragments, user input, and qualifiers enter a recorded order and window.

Generate

The model consumes that constructed sequence and produces a candidate response.

Govern

A policy or evaluation condition allows, blocks, regenerates, re-retrieves, or changes the serving path.

The trace makes retrieval quality, context construction, model behavior, and policy behavior separately testable.

Prompt ≠ assembled contextRetrieval result ≠ source documentEvaluation ≠ control actionTraining state ≠ serving state

What crosses the boundary between retrieval and generation?

A retrieval result is an object, not merely a passage. Useful fields include the fragment, source, score, query relation, rank or threshold state, and the generation step that consumes it.

  • result-object fields
  • similarity or ranking rule
  • source provenance
  • consumer

How was the model context assembled?

System instructions, retained turn state, retrieved material, user input, qualifiers, truncation, and filtering may enter in a fixed sequence. Source and order can be technically consequential.

  • context source
  • assembly order
  • window or truncation rule
  • edit feedback

What happens when a policy or evaluation condition is met?

A guardrail is legible as a branch—allow, block, or regenerate—with a defined trigger and resulting state. Evaluation can likewise trigger re-retrieval, model switching, or a degraded response.

  • decision condition
  • branch state
  • altered output
  • next action

An LLM application is not adequately described by its generated text alone. Retrieval, context construction, model execution, and the resulting control action are separate technical events.

  1. A retrieval result carries fields and provenance beyond the source passage itself.

  2. Source order, filtering, and truncation can change the constructed context without changing the model.

  3. A policy score becomes operational only when it is tied to a defined branch and next state.

  • The session and context snapshot can be reconstructed.
  • Retrieved items retain source and ranking information.
  • Evaluation thresholds and resulting actions are recorded together.