@prefix dcterms: <http://purl.org/dc/terms/> .
@prefix vcard:   <http://www.w3.org/2006/vcard/ns#> .
@prefix ftr:     <https://w3id.org/ftr#> .
@prefix dcat:    <http://www.w3.org/ns/dcat#> .
@prefix xsd:     <http://www.w3.org/2001/XMLSchema#> .
@prefix rdfs:    <http://www.w3.org/2000/01/rdf-schema#> .
@prefix dqv:     <http://www.w3.org/ns/dqv#> .
@prefix dpv:     <https://w3id.org/dpv#> .
@prefix sio:     <http://semanticscience.org/resource/> .
@prefix foaf:    <http://xmlns.com/foaf/0.1/> .
@prefix prov:    <http://www.w3.org/ns/prov#> .


# Metric Resource: SemanticCosineSimilarity
<https://w3id.org/cq4oe/metric/SemanticCosineSimilarity> a dqv:Metric, ftr:Test ;
    dcterms:identifier "https://w3id.org/cq4oe/metric/SemanticCosineSimilarity" ;
    dcterms:title "Semantic distance over dense vector representations"@en ;
    rdfs:label "SemanticCosineSimilarity: Semantic distance over dense vector representations"^^xsd:string ;
    dcat:version "0.1.0"^^xsd:string ;
    ftr:status "Active"@en ;
    dcat:landingPage <https://w3id.org/cq4oe/metric/SemanticCosineSimilarity> ;

    dcterms:description """
This metric aims to evaluate semantic similarity between a generated label and a gold-standard label by encoding each label with a pretrained sentence-transformer and computing the cosine similarity between their vector representations. The score lies in [-1, 1], with values close to 1 indicating high semantic equivalence.

**Example:**

Generate_Label_1: Carnivore

Generate_Label_2: madeFromGrape

Generate_Label_3: Software

Gold_Standard_Label_1: Predator

Gold_Standard_Label_2: usedToMake

Gold_Standard_Label_3: Wine

Result:

1. SemanticCosineSimilarity(Generate_Label_1, Gold_Standard_Label_1) ≈ 0.85
2. SemanticCosineSimilarity(Generate_Label_2, Gold_Standard_Label_2) ≈ 0.78
3. SemanticCosineSimilarity(Generate_Label_3, Gold_Standard_Label_3) ≈ 0.10

**What is being measured?**

This metric captures semantic equivalence between labels even when their surface forms differ. It is the strongest single contributor to property-level matching in pilot evaluation, because it correctly identifies paraphrases and synonyms that purely string-based methods miss.
""" ;

    dcat:keyword "Ontology Concept Matching"@en ;
    dcat:keyword "Metric"@en ;
    dcat:keyword "Classes"@en ;
    dcat:keyword "Properties"@en ;
    dcat:keyword "Encoder"@en ;
    dcat:keyword "Semantic"@en ;

    dqv:inDimension <https://w3id.org/cq4oe/dimension/ClassProperty> ;
    dcterms:isPartOf <https://w3id.org/cq4oe/task/CQ2Term> ;
    dcterms:isPartOf <https://w3id.org/cq4oe/task/CQ2Onto> ;

    ftr:hasBenchmark <https://w3id.org/cq4oe/benchmark/ALL> ;
    ftr:supportedBy <https://w3id.org/cq4oe/> ;
    dpv:isApplicableFor <https://www.wikidata.org/wiki/Q184754> ;

    dcterms:creator <https://orcid.org/0009-0001-9475-8159> ;
    dcat:contactPoint <https://orcid.org/0009-0001-9475-8159> ;
    dcterms:publisher <https://oeg.fi.upm.es> ;
    dcterms:publisher <https://ror.org/03n6nwv02> ;
    dcterms:license <http://creativecommons.org/licenses/by/4.0/> .

# Common related resources
<https://orcid.org/0009-0001-9475-8159> a vcard:Individual ;
    vcard:fn "JiaYi Li"^^xsd:string ;
    vcard:hasEmail <mailto:li.jiayi@upm.es> .

<https://oeg.fi.upm.es> a foaf:Organization ;
    rdfs:label "Ontology Engineering Group" ;
    vcard:url <https://oeg.fi.upm.es/> .

<https://ror.org/03n6nwv02> a vcard:Organization ;
    dcterms:identifier "https://ror.org/03n6nwv02" ;
    rdfs:label "Universidad Politécnica de Madrid" ;
    vcard:url <https://www.upm.es/> .

<https://w3id.org/cq4oe/benchmark/ALL> a ftr:Benchmark ;
    dcterms:title "CQ2OE Benchmark"@en ;
    dcterms:description "Competency Questions for Ontology Engineering. A benchmark for evaluating LLM-assisted ontology generation from competency questions."@en .