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30 total results found

Why knowledge graphs?

From texts to structured data: Building...

Knowledge graphs are flexible data structures which store data as (1) nodes, and (2) ties between nodes (also known as edges). Knowledge graphs as a general data structure are not limited to any particular methodology of data analysis (such as network analysis...

Finding inconsistent and invalid data

From texts to structured data: Building... Querying CASTEMO knowledge graphs

This is the collapsible text. For various reasons, such as data import or bugs of some version of the interface, a CASTEMO knowledge graph can contain inconsistent data. It is thus important to identify this data and correct the inconsistencies either manuall...

Describe your data collection choices

From texts to structured data: Building... How best collect CASTEMO data?

Every data collection campaign, even the most comprehensive CASTEMO annotation, necessarily makes choices, and is selective. In collaboration between several users, and also as time goes by, it becomes increasingly tricky to remember what data collection guid...

"Same as above": Referencing information content in CASTEMO knowledge graphs

From texts to structured data: Building... How best collect CASTEMO data?

Referring to the content of another Documents and statements often make references to other documents and statements to express that the content is the same, different, or related in other ways.  ... same, different. Treat this here. Referring to temporal a...

Querying CASTEMO knowledge graphs in Neo4j

From texts to structured data: Building... Querying CASTEMO knowledge graphs

Querying with relations

From texts to structured data: Building... Querying CASTEMO knowledge graphs

Import a full-text document and start annotating

From texts to structured data: Building... Full-text annotation

Before starting to annotate, you need to import a full text in InkVisitor, create a Resource representing this full text, and link it to a Territory. This page describes the process step by step. 1. Give a thought to your data management plan Annotation crea...

Statements

From texts to structured data: Building... Entities

Structure and purpose Statements model the syntactic structure and semantics of clauses. They have a quadruple structure with action slot and three actant slots: subject, actant1, and actant2. The semantic core is the action slot, which holds the predicate of...

Decide on the focus and extent of annotation

From texts to structured data: Building... Full-text annotation

Any semantic annotation, as comprehensive as it might be, always has a purpose, that is, is connected to a set of research questions currently pursued or considered as relevant in future work. Therefore, at the early stages of annotation, you will need to make...

Use Annotator

From texts to structured data: Building... Full-text annotation

Annotator is a component of the InkVisitor software adapted to the annotation of full-texts. Unlike most annotation tools, it is connected to a robust and historically informed entity–relationship data model, which allows you to smoothly create entities and bu...