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Question 8089: Induced Graph with Original Vertex Labels On this page Original question and givens Definition and scope Step-by-step derivation Reverse checks Result This question review and source binding Return to catalogue page 41
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This teaching derivation has second-context AI mathematical and bilingual semantic review, limited to the model and assumptions stated in this question. It has no human review or new Lean proof and does not promote the original question or MKO to Canonical truth.
R0015-08089 · q-20261012-advance-20261017-r05-graph-0089
Original question and givens Use a complete simple undirected graph on Fin(5)={0,…,4} with raw edges=[[0, 1], [0, 4]]. Endpoints are typed and loops are prohibited. Reversed or repeated edges count once; normalize endpoints and edge order. Do not infer adjacency from a drawing. Retain source subset=[4, 2, 0], normalized as a set. Give (old normalized edges, sorted retained labels, induced edges, retained-label degrees, retained-label neighbor lists).
G001 — Use a complete simple undirected graph on Fin(5)={0,…,4} with raw edges=[[0, 1], [0, 4]]. Endpoints are typed and loops are prohibited. Reversed or repeated edges count once; normalize endpoints and edge order. Do not infer adjacency from a drawing. Retain source subset=[4, 2, 0], normalized as a set. Give (old normalized edges, sorted retained labels, induced edges, retained-label degrees, retained-label neighbor lists).Definition and scope Use the original question domain, assumptions and cited MKO definitions. This item has second-context mathematical and bilingual review, with the model, answer and every arithmetic step independently recomputed from the original parameters; the source question remains a candidate.
Step-by-step derivation S001 · implies Before
n=5;raw edges=[[0, 1], [0, 4]] After
canonical edges=[[0, 1], [0, 4]] Conditions: none
Validate every simple undirected edge for typed distinct endpoints.Sort endpoints and count reversed or repeated edges once;do not infer adjacency from a drawing.
Step identifiers and dependencies Rule: simple_graph_edge_normalization · Uses: G001
S002 · implies Before
phase=original;vertex=0;all edges=[[0, 1], [0, 4]] After
neighbors=[1, 4];degree=2 Conditions: none
Scan all canonical edges.An incident edge contributes its other endpoint as a distinct neighbor.Keep original vertex labels.
Step identifiers and dependencies Rule: complete_graph_neighbor_inventory · Uses: G001, S001
S003 · implies Before
phase=original;vertex=1;all edges=[[0, 1], [0, 4]] After
neighbors=[0];degree=1 Conditions: none
Scan all canonical edges.An incident edge contributes its other endpoint as a distinct neighbor.Keep original vertex labels.
Step identifiers and dependencies Rule: complete_graph_neighbor_inventory · Uses: G001, S002
S004 · implies Before
phase=original;vertex=2;all edges=[[0, 1], [0, 4]] After
neighbors=[];degree=0 Conditions: none
Scan all canonical edges.An incident edge contributes its other endpoint as a distinct neighbor.Keep original vertex labels.
Step identifiers and dependencies Rule: complete_graph_neighbor_inventory · Uses: G001, S003
S005 · implies Before
phase=original;vertex=3;all edges=[[0, 1], [0, 4]] After
neighbors=[];degree=0 Conditions: none
Scan all canonical edges.An incident edge contributes its other endpoint as a distinct neighbor.Keep original vertex labels.
Step identifiers and dependencies Rule: complete_graph_neighbor_inventory · Uses: G001, S004
S006 · implies Before
phase=original;vertex=4;all edges=[[0, 1], [0, 4]] After
neighbors=[0];degree=1 Conditions: none
Scan all canonical edges.An incident edge contributes its other endpoint as a distinct neighbor.Keep original vertex labels.
Step identifiers and dependencies Rule: complete_graph_neighbor_inventory · Uses: G001, S005
S007 · implies Before
raw subset=[4, 2, 0];old edges=[[0, 1], [0, 4]] After
retained original labels=[0, 2, 4];induced edges=[[0, 4]] Conditions: none
Deduplicate subset labels and retain exactly original edges with both endpoints present.Do not renumber nonconsecutive labels.
Step identifiers and dependencies Rule: induced_graph_both_endpoints_guard · Uses: G001, S006
S008 · implies Before
phase=induced;vertex=0;all edges=[[0, 4]] After
neighbors=[4];degree=1 Conditions: none
Scan all canonical edges.An incident edge contributes its other endpoint as a distinct neighbor.Keep original vertex labels.
Step identifiers and dependencies Rule: complete_graph_neighbor_inventory · Uses: G001, S007
S009 · implies Before
phase=induced;vertex=2;all edges=[[0, 4]] After
neighbors=[];degree=0 Conditions: none
Scan all canonical edges.An incident edge contributes its other endpoint as a distinct neighbor.Keep original vertex labels.
Step identifiers and dependencies Rule: complete_graph_neighbor_inventory · Uses: G001, S008
S010 · implies Before
phase=induced;vertex=4;all edges=[[0, 4]] After
neighbors=[0];degree=1 Conditions: none
Scan all canonical edges.An incident edge contributes its other endpoint as a distinct neighbor.Keep original vertex labels.
Step identifiers and dependencies Rule: complete_graph_neighbor_inventory · Uses: G001, S009
Reverse checks S010 · premise_and_result_audit — Check against the original data and this step's premises; a one-way implication is not an equivalence.S009 · premise_and_result_audit — Check against the original data and this step's premises; a one-way implication is not an equivalence.S008 · premise_and_result_audit — Check against the original data and this step's premises; a one-way implication is not an equivalence.S007 · premise_and_result_audit — Check against the original data and this step's premises; a one-way implication is not an equivalence.S006 · premise_and_result_audit — Check against the original data and this step's premises; a one-way implication is not an equivalence.S005 · premise_and_result_audit — Check against the original data and this step's premises; a one-way implication is not an equivalence.S004 · premise_and_result_audit — Check against the original data and this step's premises; a one-way implication is not an equivalence.S003 · premise_and_result_audit — Check against the original data and this step's premises; a one-way implication is not an equivalence.S002 · premise_and_result_audit — Check against the original data and this step's premises; a one-way implication is not an equivalence.S001 · premise_and_result_audit — Check against the original data and this step's premises; a one-way implication is not an equivalence.Result ([[0, 1], [0, 4]], [0, 2, 4], [[0, 4]], [1, 0, 1], [[4], [], [0]]) The full substitutions and premise checks give the original answer; source identity,format and status are unchanged.
This question review and source binding Review date: 2026-10-26
Original questions, answers, step expressions, numeric ASTs and historical records are retained. Source candidate labels remain historical and are not overwritten as formal proof.
Source hashes and review receipts input commit: 0f7be61e2c22317a4075561dc822c87d881a50dboriginal question SHA-256: c85d225e37379cd6dad4327eb711655733289620db6c881d992e3261c86c4042candidate record SHA-256: d4a39780925bcd9d5dd28759914e83e2476e7b1e9a587ff3230cab75d4a7c52asemantic review receipt SHA-256: 6ecad9d909199221a07e923f87425e80b3bdec3eed46fe5910d04fca694cae18question-first witness SHA-256: e8f00458977a09493b5f9f05ab9e6feec72debaf4c7d1c609d1fc95900a35a1bLean: NOT_RUN · human review: NOT_PERFORMEDSame-source full JSON