Artificial Language

1. Core Concepts & Theoretical Blueprint

An Artificial Language question invents a made-up code language in which specific English words are represented by specific code words (often nonsense syllables), typically presented as two or more coded sentences alongside their English translations. Your task is to decode the mapping between individual English words and their corresponding code words, then use that mapping to translate a new word, phrase, or sentence that wasn't directly given.

The underlying logical structure is a set-intersection/overlap decoding system: each unique English word maps to exactly one unique code word throughout the entire problem, and the position of words within a sentence generally does NOT indicate which code word corresponds to which English word (code word order is typically scrambled relative to English word order) — meaning the only reliable decoding method is comparing which words and code words are shared across multiple given sentences.

Three decoding techniques form the complete toolkit:

• Common Word/Common Code Overlap: If exactly one English word is shared between two given sentences, the exactly one code word shared between their corresponding coded versions is that word's code — this is the single most powerful and most frequently applicable technique.
• Elimination by Process of Exclusion: Once some words in a sentence are decoded via overlap, the remaining word(s) in that sentence must correspond to the remaining, not-yet-assigned code word(s) — a direct 1-to-1 elimination.
• Triangulation Across Three-Plus Sentences: When two sentences share more than one common word (making simple overlap ambiguous), a third sentence sharing only one of those words with either of the first two can resolve the ambiguity.

Reference Table: Decoding Workflow

Step	Action	Purpose
1	List every given English sentence and its coded version side-by-side	Establish the full raw data set
2	For every pair of sentences, identify shared English words	Find candidate overlaps
3	For each shared-word pair, identify shared code words	Confirm the word-to-code mapping
4	Cross out matched words/codes from all sentences	Reduce remaining unknowns
5	Apply elimination to any sentence with only one word left undecoded	Complete the mapping

The Universal Trap: (1) Students assume code word order directly mirrors English word order (i.e., the first code word = the first English word) — this is almost NEVER a safe assumption unless the question explicitly states the code preserves word order; always rely on the overlap method instead of positional guessing. (2) Students stop decoding once they've found the ONE word the question asks about, but then fail to verify that word's code against ALL sentences it appears in — a code mapping must be consistent across every single sentence it appears in; inconsistency signals a decoding error that must be re-checked. (3) When two sentences share two or more common words, students arbitrarily guess which code word matches which English word instead of seeking out a third sentence (or additional given information) to disambiguate the pairing with certainty.

2. Exhaustive Question Typology

                            ARTIFICIAL LANGUAGE
                                    |
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      |                |                 |                 |
   Type 1            Type 2            Type 3            Type 4
 Two-Sentence        Three-or-More      Reverse           Word-Modification
 Direct Overlap       Sentence           Decoding          (Coded word to
 Decoding             Triangulation      (Code to           English, given
                                          English)           partial rules)

Type 1 — Two-Sentence Direct Overlap Decoding

Core Scenario: "'the sky is blue' = 'ta mo di ru' and 'the grass is green' = 'ta ki di so'. What is the code for 'is'?" Governing Rule/Logic: IF exactly one English word ("is") is common to both sentences THEN the exactly one code word common to both coded versions ("ta" and "di" are both common — this requires checking carefully; only the word matching exactly one common code word resolves cleanly) is that word's code — apply careful cross-checking since "the" is also common here, requiring the elimination technique across all shared words simultaneously.

Type 2 — Three-or-More Sentence Triangulation

Core Scenario: Three sentences given, each sharing exactly one word with each of the other two, allowing a complete decode of three distinct words via three separate overlaps. Governing Rule/Logic: IF sentence A and B share word X, sentence B and C share word Y, and sentence A and C share word Z THEN each pairwise overlap independently resolves one word's code, and combining all three fully decodes X, Y, and Z without ambiguity.

Type 3 — Reverse Decoding (Code to English)

Core Scenario: Given the full word-to-code mapping already established, decode a coded phrase back into English. Governing Rule/Logic: IF every code word in the given coded phrase has already been matched to an English word THEN simply substitute each code word with its corresponding English word — no positional reordering is needed unless the question explicitly requires grammatically correct English word order.

Type 4 — Word-Modification / Partial Rule Application

Core Scenario: "In a code language, 'CATS' is written as 'DBUT'. Using the same rule, how is 'DOGS' written?" Governing Rule/Logic: IF the coding rule operates on individual letters (each letter shifted +1: C+1=D, A+1=B, T+1=U, S+1=T) THEN apply that identical letter-level rule to the new word: D+1=E, O+1=P, G+1=H, S+1=T, giving EPHT.

3. Type-wise Practice MCQs with Full Solutions

Type 1 — Two-Sentence Direct Overlap Decoding

Q1. If "pen is mighty" is coded as "zil kop tan" and "sword is sharp" is coded as "vec kop rul", what is the code for "is"? (A) zil (B) kop (C) tan (D) vec

Correct Answer: (B) kop Solution: "is" is the only word common to both English sentences. "kop" is the only code word common to both coded sentences. Therefore, "is" = "kop".

Q2. If "birds can fly" is coded as "nim dor pal" and "fish can swim" is coded as "dor rok sil", what is the code for "can"? (A) nim (B) dor (C) pal (D) rok

Correct Answer: (B) dor Solution: "can" is the only word common to both English sentences. "dor" is the only code word common to both coded sentences. Therefore, "can" = "dor".

Q3. If "the cat sat" is coded as "mu ta ke" and "the dog ran" is coded as "mu bo ye", what is the code for "the"? (A) mu (B) ta (C) ke (D) bo

Correct Answer: (A) mu Solution: "the" is the only word common to both English sentences. "mu" is the only code word common to both coded sentences. Therefore, "the" = "mu".

Type 2 — Three-or-More Sentence Triangulation

Q1. "apple is sweet" = "lin zop rav"; "sweet is nice" = "zop rav tik"; "nice is fine" = "tik rav dez". Find the code for "sweet", "is", and "nice". (A) sweet=lin, is=rav, nice=zop (B) sweet=zop, is=rav, nice=tik (C) sweet=zop, is=tik, nice=rav (D) sweet=rav, is=zop, nice=tik

Correct Answer: (B) sweet=zop, is=rav, nice=tik Solution: "is" appears in all three sentences; "rav" appears in all three coded versions — so "is"="rav". Comparing sentence 1 and 2, both share "sweet" and "is"; since "is"="rav" is already fixed, the remaining common code word "zop" must be "sweet" (as "zop" appears in both sentence 1 and 2's codes, matching "sweet" appearing in both). Comparing sentence 2 and 3, both share "is" and "nice"; since "is"="rav" is fixed, the remaining common code word "tik" must be "nice".

Q2. "red car fast" = "hin bol zeg"; "blue car slow" = "hin cav mip"; "red bike slow" = "zeg dun mip". Find the code for "car", "red", and "slow". (A) car=hin, red=zeg, slow=mip (B) car=bol, red=zeg, slow=mip (C) car=hin, red=mip, slow=zeg (D) car=zeg, red=hin, slow=mip

Correct Answer: (A) car=hin, red=zeg, slow=mip Solution: Sentences 1 and 2 share "car"; their common code word is "hin" (present in both) — so "car"="hin". Sentences 2 and 3 share "slow"; their common code word is "mip" — so "slow"="mip". Sentences 1 and 3 share "red"; their common code word is "zeg" — so "red"="zeg".

Q3. "sun gives heat" = "tor bim wex"; "fire gives light" = "kol bim sav"; "sun gives light" = "tor bim sav". Find the code for "sun", "gives", and "light". (A) sun=tor, gives=bim, light=sav (B) sun=bim, gives=tor, light=sav (C) sun=tor, gives=sav, light=bim (D) sun=sav, gives=bim, light=tor

Correct Answer: (A) sun=tor, gives=bim, light=sav Solution: "gives" appears in all three sentences; "bim" appears in all three coded versions — so "gives"="bim". Sentences 1 and 3 share "sun" and "gives"; since "gives"="bim" is fixed, the remaining shared code "tor" must be "sun". Sentences 2 and 3 share "light" and "gives"; since "gives"="bim" is fixed, the remaining shared code "sav" must be "light".

Type 3 — Reverse Decoding (Code to English)

Q1. Given the established mapping: sun=tor, gives=bim, light=sav, fire=kol. Decode the coded phrase "kol bim sav" into English. (A) fire gives light (B) light gives fire (C) sun gives light (D) fire has light

Correct Answer: (A) fire gives light Solution: Substitute directly: kol=fire, bim=gives, sav=light. The coded phrase "kol bim sav" decodes word-for-word to "fire gives light".

Q2. Given the established mapping: car=hin, red=zeg, slow=mip, bike=dun. Decode the coded phrase "zeg dun mip" into English. (A) red car slow (B) red bike slow (C) slow red bike (D) bike red slow

Correct Answer: (B) red bike slow Solution: Substitute directly: zeg=red, dun=bike, mip=slow. The coded phrase "zeg dun mip" decodes to "red bike slow" (matching English word order as originally given for this specific sentence).

Q3. Given the established mapping: apple=lin, sweet=zop, is=rav, nice=tik. Decode the coded phrase "lin rav zop" into English. (A) apple is sweet (B) sweet is apple (C) apple is nice (D) nice is sweet

Correct Answer: (A) apple is sweet Solution: Substitute directly: lin=apple, rav=is, zop=sweet. The coded phrase "lin rav zop" decodes to "apple is sweet".

Type 4 — Word-Modification / Partial Rule Application

Q1. In a code language, "LAMP" is written as "MBNQ". Using the same rule, how is "DESK" written? (A) EFTL (B) EFUL (C) DFTL (D) EFTM

Correct Answer: (A) EFTL Solution: Each letter shifts +1: L+1=M, A+1=B, M+1=N, P+1=Q, confirming the rule. Applying to DESK: D+1=E, E+1=F, S+1=T, K+1=L, giving EFTL.

Q2. In a code language, "STONE" is written as "TSPMF". Using the same rule (each letter's position alternates +1/−1), how is "PLANT" written? (A) QKBMU (B) QKBOS (C) OKBMU (D) QLBMU

Correct Answer: (A) QKBMU Solution: Verify the rule: S(pos1)+1=T, T(pos2)−1=S, O(pos3)+1=P, N(pos4)−1=M, E(pos5)+1=F — confirms alternating +1/−1 starting with +1 at odd positions. Applying to PLANT: P(pos1)+1=Q, L(pos2)−1=K, A(pos3)+1=B, N(pos4)−1=M, T(pos5)+1=U, giving QKBMU.

Q3. In a code language, "HOUSE" is written as "IPVTF". Using the same rule, how is "MOUSE" written? (A) NPVTF (B) MPVTF (C) NPVTG (D) NPWTF

Correct Answer: (A) NPVTF Solution: Each letter shifts +1: H+1=I, O+1=P, U+1=V, S+1=T, E+1=F, confirming the rule. Applying to MOUSE: M+1=N, O+1=P, U+1=V, S+1=T, E+1=F, giving NPVTF.

4. High-Yield Speed Tricks & Shortcut Mental Models

Shortcut 1: Underline-and-Match Overlap Scan Application: For every pair of given sentences, physically (or mentally) underline every English word appearing in both, then underline every code word appearing in both coded versions — match them up in the SAME left-to-right order they were underlined only after confirming the counts match exactly. Mental Model: This turns an abstract "find the pattern" task into a mechanical visual matching exercise; when the number of underlined English words equals the number of underlined code words across a sentence pair, the mapping is directly readable without further ambiguity, and any mismatch in count immediately signals you need a third sentence for triangulation.

Shortcut 2: Consistency Cross-Check Before Finalizing Application: After decoding the specific word the question asks about, verify that word's assigned code word actually appears (in that exact form) in every single given sentence where the English word appears — treat any mismatch as a signal to redo the decoding. Mental Model: Because a valid code mapping must be 100% consistent throughout the entire problem, a final consistency check across ALL given sentences (not just the two you used to derive the answer) acts as a free built-in error-detection step, catching mistakes before you commit to a final answer.

5. Deep-Dive: Most Frequently Asked Questions (Exam-Style Walkthroughs)

Problem 1 (SSC/RRB Level): If "book is knowledge" is coded as "fa lo mi" and "knowledge brings power" is coded as "lo tuk vex", find the code for "knowledge".

Traditional Method (Slow) — approx. 25-30 seconds: A slow solver reads both sentences and both codes, tries to match words to codes purely by position (assuming the first English word matches the first code word), incorrectly guessing "book"="fa" based on position alone without verifying via overlap, and only realizes the error when the answer doesn't fit logically with the second sentence.

Exam Shortcut (Fast) — approx. 8 seconds: Apply the Underline-and-Match Overlap Scan directly: "knowledge" is the only word common to both sentences. "lo" is the only code word common to both coded versions. Answer: "knowledge" = "lo". No positional guessing is needed — the overlap method resolves it immediately and unambiguously.

Problem 2 (UPSC/Banking Advanced Level): In a code language: "global trade boosts economy" = "wex jop nil tas"; "economy affects global growth" = "nil ruv wex fom"; "trade affects growth patterns" = "jop ruv fom biv". Decode the code for "trade", "economy", "global", and "growth".

Step-by-step derivation:

1. List word frequencies across all three sentences: "global" appears in sentences 1 and 2. "trade" appears in sentences 1 and 3. "economy" appears in sentences 1 and 2. "growth" appears in sentences 2 and 3. "affects" appears in sentences 2 and 3.
2. Sentences 1 and 2 share TWO words: "global" and "economy" — their codes share exactly two code words: "wex" and "nil". This is ambiguous on its own (we know {global, economy} = {wex, nil} as a set, but not which is which).
3. Resolve the ambiguity using sentence 3: sentence 2 and 3 share TWO words as well: "growth" and "affects" — their codes share "ruv" and "fom". Again ambiguous alone for this pair.
4. Use sentence 1 and 3 to resolve "trade": they share only ONE word, "trade" — check their codes ("wex jop nil tas" and "jop ruv fom biv") for the one shared code word: "jop" is common to both. Therefore "trade" = "jop" (fully resolved, unambiguous).
5. With "trade"="jop" now fixed, return to sentence 1 ("wex jop nil tas" = "global trade boosts economy"): remove "trade"="jop", leaving "wex nil tas" for "global boosts economy". We still need one more distinguishing clue to separate "global" and "economy" from "wex" and "nil".
6. Return to sentence 2 and 3 overlap ("growth" and "affects" sharing "ruv" and "fom"): since "trade"="jop" is now known and doesn't appear in sentences 2 or 3, this doesn't directly help distinguish growth/affects yet — instead, use the fact that "affects" appears in BOTH sentence 2 and 3, while "growth" also appears in BOTH — still ambiguous without further info, confirming this specific artificial construction leaves "affects" vs "growth" and "global" vs "economy" as genuinely two internally-ambiguous pairs unless the question additionally specifies one individual word's code directly (as real exam questions typically do to avoid this residual ambiguity) — for the purposes of this walkthrough, note that "trade" is cleanly and fully decodable via the single-word-overlap method (step 4), while "global," "economy," "growth," and "affects" would require one additional given clue (a fourth sentence or a direct single-word statement) to fully disambiguate within their respective two-word overlap pairs.

Final Answer: "trade" = "jop" is fully and unambiguously decoded. "global" and "economy" are known to jointly correspond to {"wex", "nil"} but require an additional sentence to assign individually; similarly "growth" and "affects" jointly correspond to {"ruv", "fom"} pending further disambiguation — this walkthrough deliberately illustrates a genuine limitation case, reinforcing the Universal Trap warning that two-word overlaps between only two sentences are never sufficient alone and must be resolved via a third distinguishing sentence before an individual word's code can be confidently finalized.

6. Chapter Checklist for Students

• I use the Underline-and-Match Overlap Scan on every sentence pair, never assuming code word order mirrors English word order.
• I seek a third (or further) sentence for Triangulation whenever two sentences share more than one common word, rather than guessing the pairing.
• I perform the Consistency Cross-Check across every sentence where a decoded word appears before finalizing any answer.
• I apply letter-level shift rules (Word-Modification type) mechanically and verify them against the full given example before applying to a new word.
• I explicitly recognize when a given set of sentences is insufficient to fully disambiguate every word, rather than forcing a guess where genuine ambiguity remains.