structure/ancestor
need secondary inputs: true
definition: Generate new candidates by looking for 1 or more ancestors that have already been mapped.
subclass of: CandidateGenerator

label/splitted source
definition: A label matcher matching after compound splitting the label(s) of the source concepts. Source labels are splitted using rdf_tokenize_literal/2. Warning: source label tokens are matched against complete target labels!
subclass of: CandidateGenerator

structure/descendent
need secondary inputs: true
definition: Generate new candidates by looking for 1 or more descendents that have already been mapped.
subclass of: CandidateGenerator

label/exact
definition: Generate new candidates based on exact matching labels of source and target concepts.
subclass of: CandidateGenerator

label/similarity
definition: Generate new candidates based on similar labels. The matcher is based on the 'isub' metric introduced in 'A string metric for ontology alignment' by Giorgos Stoilos, 2005.
subclass of: CandidateGenerator

numeric/difference
definition: Generate new candidates based on similar numeric literals. The score is the absolute difference of the two numeric literals compared, or infinite if these are not numbers.
subclass of: CandidateGenerator

import/preloaded
definition: Match mappings from preloaded named graph against concepts in source and target vocabularies
subclass of: CandidateGenerator

structure/related
need secondary inputs: true
definition: Generate new candidates by looking for 1 or more related concepts that have already been mapped.
subclass of: CandidateGenerator

label/stemmed
definition: Generate new candidates based on label matching after (snowball) stemming.
subclass of: CandidateGenerator

structure/ancestor
need secondary inputs: true
definition: Select mappings with the most mapped ancestors, discard others for the same source/target. If type=all, all correspondences with one or more ancestors are selected.
subclass of: MappingPartitioner

label/compound source
definition: Select mappings with the most matching labels, discard others for the same source/target. If type=all, all candidates with matching labels are selected. All matching is done after compound splitting the label(s) of the source concepts. Source labels are splitted using rdf_tokenize_literal/2. Warning: source label tokens are matched against complete target labels!
subclass of: MappingPartitioner

structure/descendent
need secondary inputs: true
definition: Select mappings with the most mapped descendents, discard others for the same source/target. If type=all, all correspondences with one or more descendents are selected.
subclass of: MappingPartitioner

label/exact
definition: Select mappings with the most matching labels, discard others for the same source/target. If type=all, all candidates with matching labels are selected.
subclass of: MappingPartitioner

label/similarity
definition: Select mappings with the most similar labels, discard others for the same source/target. If type=all, all candidates with sufficiently similar labels are selected. The matcher is based on the 'isub' metric introduced in 'A string metric for ontology alignment' by Giorgos Stoilos, 2005.
subclass of: MappingPartitioner

numeric/difference
definition: Select mappings with similar numeric literals. If type=all, all candidates with sufficiently similar numbers are selected. The score is the absolute difference of the two numeric literals compared, or infinite if these are not numbers.
subclass of: MappingPartitioner

import/preloaded
definition: Select mappings with corresponding mappings in the preloaded mapping, discard others with the same source/target.
subclass of: MappingPartitioner

structure/related
need secondary inputs: true
definition: Select mappings with the most mapped related concepts, discard others for the same source/target. If type=all, all correspondences with one or more related concepts are selected.
subclass of: MappingPartitioner

label/stemmed
definition: Select mappings with the most matching labels after (snowball) stemming, discard others for the same source/target. If type=all, all candidates with matching labels are selected.
subclass of: MappingPartitioner

ambiguity/remove
definition: Select correspondences with a unique source, target or both, discard others
subclass of: MappingPartitioner

sampler
materialize: always
definition: Component that randomly samples correspondences to create a new mapping.
comment: Samples are always materialized to guarantee replicability of the workflow.
subclass of: MappingPartitioner

best numeric score
definition: Select correspondences that have the best score considering some numerical ranking, discard others.
subclass of: MappingPartitioner

most generic
definition: Select the most generic concepts among alternatives for the same source/target, discard others.
subclass of: MappingPartitioner

most labels
definition: Select correspondences that already have the most matching labels (according to their evidence data.)
subclass of: MappingPartitioner

most methods
definition: Select correspondences that have been selected by the most other methods (according to their evidence data.)
subclass of: MappingPartitioner

sibling selecter
definition: Select the siblings (if any) among alternatives for the same source/target. This is used, for example, when a single source with two labels matches on two distinct but very similar targets and both mappings need to be preserved.
subclass of: MappingPartitioner

partition mapped/unmapped
need secondary inputs: true
definition: Partition a vocabulary based on the concepts having already been mapped, or not.
subclass of: VirtualVocabPartitioner

partition facet on type
definition: Partition a vocabulary based on the concepts being of a specific type, or not.
subclass of: VirtualVocabPartitioner

partion facet on property/value
definition: Partition a vocabulary based on the concepts having a specific property/value, or not.
subclass of: VirtualVocabPartitioner

partition facet by subtree
definition: Partition a vocabulary based on the concepts being in the sub-tree below (using BT/NT) a common parent concept, or not.
subclass of: VirtualVocabPartitioner

partition on unique labels
definition: Partition a vocabulary based on the concepts being uniquely labeled, or not.
subclass of: VirtualVocabPartitioner

Manual evaluation
definition: A process class representing manual evaluation processes
subclass of: Process

mapping merger
need secondary inputs: true
definition: Merge two or more mappings into one new mapping. For example, to collect the good mappings made by different processes.
subclass of: SetOperator

overlap
need secondary inputs: true
definition: Component that analyzes a set of mappings by creating intersections and differences sets
subclass of: SetOperator

evaluater
definition: Component that analyzes correspondences in a mappings by manual evaluation
subclass of: Analyzer