bill
b758d7ea60
- src/types.hpp: complete UCWM type system in C++20 — 19 enums, 11 facet data types, all core structs (CanonicalObject, Constraint, Facet, GateSignal, WorldState, etc.) with full JSON round-trip serialization - src/main.cpp: smoke test — constructs apple-problem WorldState by hand, serializes to JSON - tests/test_types.cpp: 19 tests, 123 assertions, all passing - CMakeLists.txt: CMake + CPM build with nlohmann/json, spdlog, Catch2 - schemas/: JSON Schema contracts for all UCWM data types - gates/, specialists/, resolver/, synthesis/: language-agnostic interface contracts and domain specs for all pipeline layers - docs/: architecture, vocabulary, decision matrices, roadmap (6 phases, 28 sprints), sprint_001, implementation_constraints Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
118 lines
3.0 KiB
Markdown
118 lines
3.0 KiB
Markdown
# Temporal Specialist
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**specialist_id:** `temporal`
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**trigger_gates:** `has_temporal_relation`, `has_state_change`
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---
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## Responsibility
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The temporal specialist adds before/after/during/recurring constraints to events and states. It identifies time points, intervals, and orderings, then attaches TemporalFacets to relevant objects and emits temporal ordering constraints.
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---
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## Manifest
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```
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declared_facet_kinds:
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- temporal
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declared_constraint_types:
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- before
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- after
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- during
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- overlaps
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- starts_at
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- ends_at
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- recurring
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budget_caps:
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max_objects_proposed: 4
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max_facets_emitted: 8
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max_constraints_emitted: 12
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max_merges: 0
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max_splits: 0
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```
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---
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## Output: TemporalFacet
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Attach to any object of kind `event`, `state`, or `procedure_step`.
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```
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TemporalFacet fields used:
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- time_point: absolute or relative (if known)
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- interval_start: if event has a duration
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- interval_end: if event has a duration
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- temporal_order_refs: constraint_ids expressing ordering
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- is_recurring: true/false
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- recurrence_pattern: if recurring
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```
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---
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## Output: Constraints
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### `before(A, B)`
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Event or state A occurs before event or state B.
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Emit when:
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- Explicit connective: `before`, `prior to`, `earlier`, `first ... then`
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- Narrative sequence: events described in causal or sequential order
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- Completed event followed by a subsequent event
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Strength: `hard` for explicit connectives, `soft` for narrative inference.
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### `after(A, B)`
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Event A occurs after event B. Equivalent to `before(B, A)` but retains the original linguistic direction.
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### `during(A, B)`
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Event A occurs within the span of event B.
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### `overlaps(A, B)`
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Events A and B share some time without one being fully within the other.
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### `starts_at(E, time_expression)`
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Argument_refs: [event_id, time_object_id]. Emit when a specific start time is mentioned.
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### `ends_at(E, time_expression)`
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Argument_refs: [event_id, time_object_id]. Emit when a specific end time is mentioned.
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### `recurring(E, pattern)`
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Emit when an event is described as habitual or recurring. Argument_refs: [event_id, pattern_string_as_object].
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---
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## Ordering baseline algorithm
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```
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events = [objects in target_refs where kind = event | state | procedure_step]
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for each pair (A, B) in events × events where A ≠ B:
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check for explicit temporal connective between A and B
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if found:
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emit corresponding constraint with strength = hard
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else:
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check narrative order (A mentioned before B in text):
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if A is a precondition or cause of B:
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emit before(A, B) with strength = soft
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```
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---
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## Contract test requirements
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- Given `Alice had 5 apples. She gave Bob 2 apples.`, must emit `before(EV_initial_possession, EV_transfer)` or equivalent
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- Given explicit `before X, Y happened`, must emit `before(Y, X)` with `strength: hard`
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- Must not emit entity, quantity, or ownership constraints
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- All temporal facets must reference at least one constraint
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- All emitted constraints must have `source_module: temporal`
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