Strategic Logic Framework for Reading Comprehension

Structural Reading and Logical Mapping

Apply a greedy algorithm to text analysis: prioritize the simplest, shortest sentence within a logical block to identify test nodes. English expository writing follows a linear thinking principle: abstract concepts precede specific details, with the first paragraph and the leading sentence of subsequent paragraphs carrying the core thesis.

Forward Logic (Synonymous Progression)

Sequential relationships indicate that sentences share equivalent semantic values. Validate the simplest node to locate the answer.

• Continuation: then, subsequently
• Coordination: and, or, semicolon (;)
• Exemplification: for example, such as, including
• Progression: furthermore, moreover, additionally
• Causality: because, since, thus, therefore, so...that, by (meaning through)
• Definition/Explanation: is, are, as, in, of, colon (:), parentheses, dash (-)

Reverse Logic (Contrasting Progression)

Contradictory relationships indicate that the final node in the sequence holds the ultimate emphasis (A paves the way for B, B for C; C is the core). Always validate the last reverse-logic node first.

• Transition: but, however, yet, while, though, although, whereas
• Negation: not, seemingly, it seems
• Concession: despite, admittedly
• Contrast: by contrast, by comparison, unlike

Execution Protocol: If a paragraph combines multiple logics (e.g., A+B-C+D), merge forward nodes (A', C'). Validate the last reverse node's simplest sentence first.

Vocabulary Resolution Engine

When direct lexical knowledge fails, deploy structural reading or morphological analysis.

1. Part-of-Speech Alignment: Match verbs to verbs, adjectives to adjectives.
2. Contextual Logic Mapping: Identify forward/reverse logic markers around the target word. Find the physically closest, structurally simplest word of the same part of speech. Apply synonymous or antonymous matching based on the logic direction.
3. Morphological Decomposition: Leverage affixes and roots for semantic inference.

Affix and Root Reference Matrix

Negative/Downward:
de- (down/decline), in-/im-/il-/ir-/un-/ne-/dis- (negation), ex- (out/exclude)

Positive/Forward:
pro- (forward/positive), sur- (over/exceed)

Quantity/State:
uni- (single/uniform), hetero- (different), homo- (same), diver-/var- (diverse/change), com-/co- (together/joint), re- (again), mini- (small), auto- (self/automatic)

Transformation:
alt- (change), ex-ten- (extend/stretch)

Fact and Negative Fact Information Processing

Identify via "According to..." (Fact) or "Not/Except" (Negative Fact). Employ the Golden Eight-Step Protocol.

Golden Eight-Step Protocol

1. Structural Skim: Map paragraph logic (Forward/Reverse) within 20 seconds.
2. Anchor Extraction: Isolate 3+1+1 anchors from the prompt and options.
   • Tier 1: Proper nouns, dates, locations.
   • Tier 2: Content nouns.
   • Tier 3: Distinctive modifiers (e.g., "first").
   • Avoid: "Seaweed" anchors (overly broad terms appearing at paragraph starts).
3. Intersection Localization: Use multi-anchor linkage (find the intersection where anchors converge) scanning three lines at a time.
4. Keyword Alignment: Identify the logical query (e.g., "why" -> "because"; "explain" -> conclusion markers).
5. Contextual Match: Align keywords with the localized text segment.
6. Logic Segmentation: Isolate the target zone. If text presents A [Coordinate/Contrast/Progression] B, and the query targets A, any option referencing B is nullified.
7. Core Node Matching: Verify the main clause (ignore subordinate clauses) against options.
8. Counter-Deduction: Eliminate options via false logic traps (absolute terms, invalid comparisons).

Negative Fact Strategy

Locate the distribution of parallel structures (e.g., First, Second, Third; or time sequences 1860, 1890). Match the three valid parallel components to eliminate them, revealing the divergent option.

Inference and Sentence Simplification Protocols

Inference Logic

Triggered by infer/imply/suggest. Utilize forward inference (similar traits) or reverse inference (contradictory traits, signaled by unlike/contrast). Due to high paraphrasing complexity in correct options, prioritize elimination using logic segmentation and false logic detection.

Sentence Simplification Hierarchy

Match structural logic before semantic content.

Logic Priority: Transition > Causality > Coordination > Negation.

Scope Priority: Inter-sentence logic (between punctuation) > Intra-sentence logic.

Positional Priority: Central logic markers > Peripheral logic markers.

1. Round 1 Elimination: Identify primary central logic in the source sentence. Discard options lacking this logic.
2. Round 2 Elimination: Align secondary inner logic.
3. Round 3 Elimination: Match main clause entities (subject/object nodes), discarding subordinate clause noise (e.g., "such as" clauses).

Rhetorical Purpose and Reference Resolution

Rhetorical Purpose (Interface Mapping)

Queries author intent (e.g., "Why does the author mention X?"). 90% involve Premise-Evidence mapping.

• Rule of Proximity: Linear thinking dictates abstract premise precedes specific evidence. If the highlighted text is specific (contains proper nouns, dates), scan immediately backward for the abstract premise.
• Interface Markers: "For example", "such as", or implied instantiation.
• Paragraph-Level: If querying paragraph structure, read the leading sentence.

Reference Node Tracking

Identify via "refers to".

1. Analyze syntax (singular/plural, person) of the referent.
2. Apply Linear/Forward-Looking Principle: Target the subject or nearest noun in the preceding sentence.
3. Default search zone: The same sentence. If the referent begins a sentence or forms a pronoun chain, extend search to the previous sentence.
4. Semantic Validation: Substitute the referent into the sentence to ensure logical consistency.

Sentence Insertion and Main Idea Synthesis

Sentence Insertion Algorithm

1. Pronoun Hook: Locate demonstrative/personal pronouns (this, these, they) in the insertion block. The preceding block must contain the antecedent noun.
2. Linear Progression: Map general-to-specific sequences. Insert general statements before specific manifestations.
3. Logic Segmentation: Ensure insertion does not sever tightly coupled logic blocks (e.g., coordinate pairs).

Main Idea Extraction

Select summary options (6-choose-3 or 7-choose-5) via exclusion.

• Eliminate Minor Nodes: Options dwelling on granular details or isolated examples are invalid.
• Eliminate Absolutes: Words like "only", "most", "must" invalidate options unless textually supported.
• Eliminate Divergent Logic: Options contradicting the introductory sentence's thesis or lacking its core entities are invalid.