ucwm/gates/simple_rules.md

Simple Rule-Based Gate Definitions

This file specifies the rule logic for the initial rule-based gate implementations. These are starter gates — high-recall, zero training cost, acceptable false positive rate.

Each gate spec below is language-agnostic. Any implementation must produce identical GateSignal outputs for the given inputs.

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Gate: is_math

Detects: numeric computation, arithmetic, algebra, equations.

Rule logic:

1. Activate if input contains any digit sequence (regex: \d+)
2. Activate if input contains math keywords: how many, total, sum, difference, product, divided by, minus, plus, equals, more than, less than, percent, ratio
3. Activate if input contains operator symbols: +, -, *, /, =, %, ^

Confidence assignment:

• Multiple signals present → 0.95
• One signal, multiple instances → 0.85
• One signal, one instance → 0.70

---

Gate: has_entity_reference

Detects: named or implied entities (people, organizations, places, objects, artifacts).

Rule logic:

1. Activate if any token starts with a capital letter and is not the first word of the sentence
2. Activate if input contains proper-noun indicators: Mr., Ms., Dr., the, followed by capitalized noun
3. Activate if input contains pronouns: he, she, they, it, him, her, them
4. Activate if input contains possessive markers: Alice's, Bob's, its

Confidence assignment:

• Capital-letter token found → 0.90
• Pronoun only → 0.75
• Neither, but possessive marker found → 0.80

---

Gate: has_quantity

Detects: counts, amounts, measures, percentages, ordinals.

Rule logic:

1. Activate if input contains a digit sequence
2. Activate if input contains number words: one, two, three, ... ten, hundred, thousand, million
3. Activate if input contains measure words: apples, dollars, meters, kilograms, minutes, hours, days
4. Activate if input contains ordinals: first, second, third, last

Confidence assignment:

• Digit + measure word → 0.99
• Digit only → 0.85
• Number word only → 0.80

---

Gate: has_ownership_transfer

Detects: give, sell, take, receive, lose, transfer of possession.

Rule logic:

1. Activate if input contains transfer verbs: give, gave, gives, take, took, takes, sell, sold, sells, receive, received, receives, lose, lost, loses, transfer, transferred, hand, handed, pass, passed
2. Activate if input contains indirect-object patterns: gave [entity] [object], [entity] sold [object] to [entity]

Confidence assignment:

• Transfer verb present → 0.92
• Indirect-object pattern confirmed → 0.97

---

Gate: has_temporal_relation

Detects: before/after/during/recurring/sequential ordering.

Rule logic:

1. Activate if input contains temporal connectives: before, after, during, when, then, next, later, previously, first, second, finally, since, until, while
2. Activate if input contains time expressions: yesterday, tomorrow, at noon, on Monday, day/month/year patterns
3. Activate if input contains sequence markers: step 1, then, afterward, subsequently

Confidence assignment:

• Temporal connective + time expression → 0.97
• Temporal connective only → 0.82
• Sequence marker only → 0.75

---

Gate: has_logical_negation

Detects: not, never, unless, except, no, without, deny, false.

Rule logic:

1. Activate if input contains negation words: not, no, never, none, neither, nor, without, unless, except, deny, denied, false, incorrect, wrong
2. Activate if input contains negative contractions: isn't, aren't, wasn't, weren't, doesn't, don't, didn't, can't, won't, wouldn't, couldn't, shouldn't

Confidence assignment:

• Negation word found → 0.92

---

Gate: has_causal_relation

Detects: cause, effect, enable, block, because, therefore, so.

Rule logic:

1. Activate if input contains causal connectives: because, therefore, so, thus, hence, consequently, as a result, due to, caused by, leads to, results in, enables, prevents, blocks, allows

Confidence assignment:

• Causal connective found → 0.90

---

Gate: has_coreference

Detects: pronouns and aliases that refer to previously mentioned entities.

Rule logic:

1. Activate if input contains personal pronouns: he, she, they, it, him, her, them, his, hers, their, its
2. Activate if input contains demonstrative references: this, that, these, those followed by a noun that was mentioned earlier
3. Activate if multiple entities are named AND pronouns are present

Confidence assignment:

• Pronoun present + multiple named entities → 0.90
• Pronoun only, single entity → 0.70

---

Gate: has_spatial_relation

Detects: location, containment, direction, proximity.

Rule logic:

1. Activate if input contains spatial prepositions: in, at, on, above, below, inside, outside, near, far, left, right, north, south, east, west, between, next to, adjacent to
2. Activate if input contains place names (capitalized geographics) or location indicators: street, city, country, room, building, floor

Confidence assignment:

• Spatial preposition + place indicator → 0.92
• Spatial preposition only → 0.72

---

Gate: has_planning

Detects: goals, steps, prerequisites, sequencing of actions.

Rule logic:

1. Activate if input contains planning vocabulary: plan, goal, step, procedure, prerequisite, depends on, requires, in order to, so that, to achieve
2. Activate if input contains numbered or ordered list markers

Confidence assignment:

• Planning vocabulary present → 0.88

---

Gate: has_social_intent

Detects: beliefs, desires, obligations, deception, trust, social roles.

Rule logic:

1. Activate if input contains mental state verbs: believe, believes, think, thinks, want, wants, know, knows, intend, intends, expect, expects, hope, hopes
2. Activate if input contains obligation/permission words: must, should, ought, may, allowed, permitted, required, obligated
3. Activate if input contains social verbs: promise, lie, deceive, trust, cooperate, compete, agree, refuse

Confidence assignment:

• Mental state verb present → 0.85
• Obligation/permission word → 0.80
• Social verb → 0.90

---

Gate: requires_external_knowledge

Detects: queries that require facts not present in the input text.

Rule logic:

1. Activate if input contains knowledge-seeking patterns: who is, what is, where is, when did, how does, why does combined with named entities
2. Activate if input references historical events, scientific facts, or world geography without providing context

Note: This gate has higher false-positive tolerance than most. When uncertain, fire.

Confidence assignment:

• Knowledge-seeking pattern with named entity → 0.85
• Named entity without provided context → 0.70

---

Gate: requires_synthesis_only

Detects: inputs that are complete, self-contained, and require no structural decomposition.

Rule logic:

1. Activate only if all of the following hold:
   • No other gates fire with confidence > 0.70
   • Input is a direct factual statement with no quantities, entities, or relations to track
   • Input length < 15 tokens

Note: This gate is a low-priority catch-all. It should rarely fire when other gates fire.

Confidence assignment:

• All conditions met → 0.80

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Implementation notes

• All keyword lists should be treated as seed lists. Implementors should extend them for their target domain.
• Case-insensitive matching is preferred.
• Lemmatization or stemming is recommended for verb forms.
• Do not hardcode language; design for swappable tokenizers and keyword tables.