PAT Refactored Data

2-13-22 Clean Sheet

This visualization renders a semantic knowledge graph from linguistic JSON data, showing propositional relationships such as predicates, referents, and nested clauses. It builds nodes and links recursively from the `ContextTrackingData` structure, using D3 v4’s force simulation to layout the graph. The rendering combines SVG for nodes and links with Canvas 2D text measurement to size labels. WebCola is also loaded, though the primary layout is driven by `d3.forceSimulation`. The example demonstrates hierarchical clause decomposition, including recursive structures for reported speech and causation.

Pat working file

This example demonstrates a force-directed graph of linguistic role annotations, where nodes representing words are grouped into colored, rounded rectangles based on syntactic relations. Users can drag nodes to reposition them, with double-clicking releasing a node from its fixed position. The visualization uses WebCola’s constraint-based layout through its D3 adapter, combining SVG for rendering nodes, links, and group bounds. The code relies on `d3.json` to load the graph data and `d3.zoom` for panning, with node sizes defined in the JSON input.

Fork of 2-13-22 Clean Sheet

This visualization renders a hierarchical knowledge graph from JSON-encoded semantic parses of sentences, showing predicates, arguments, and nested propositional structures. It uses d3.v4 with forceSimulation for layout, rendering nodes and links as SVG elements, while Canvas is used to measure text dimensions for label sizing. Nodes represent nucleus predicates, referents, and modifiers, with links connecting arguments to their cores. The example loads data via d3.json and constructs the graph by iterating through the ContextTrackingData array, handling nested clauses and referent phrases.

Visualization

This visualization shows the bipartite clause structure of an English sentence, using a force-directed graph to lay out words grouped by their grammatical roles (effector, theme, predicate, periphery). The graph displays nodes for each word or phrase, with links connecting core arguments to the predicate, and colored rectangles grouping related units like the core and clause. It uses D3’s `forceSimulation` with a many-body strength, and for layout it relies on the WebCola library via `d3adaptor` to handle grouping and overlap avoidance. The data is structured JSON from the meaning matcher, and the canvas is used to measure text width for node sizing.

2-19-2022 rework

This visualization reworks semantic JSON knowledge structures into an interactive graph of nodes, links, and groups. It displays the logical relationships within sentences, such as "the shark bit the surfer savagely," by parsing hierarchical data from files like `example.json` and `happycat.json`. The code uses D3 v4’s `d3.json` to load data, creates nodes with varying widths based on text measurement via Canvas `measureText`, and employs WebCola for force-directed layout. SVG and Canvas contexts render the graph, with node types distinguishing referents, predicates, and groupings.

70% match

Graph Test

This graph diagram visualizes the network of connections within the Kenneth Rainin Foundation, representing predicates, referents, and groups as colored rectangular nodes. The visualization uses D3.js v6 with `forceSimulation` to position nodes, `forceManyBody` for repulsion, `forceLink` for edge constraints, and `forceCenter` for layout anchoring. Nodes are rendered as SVG rectangles with drag interactions, while links appear as lines between connected elements. The data is defined programmatically in data.js, with a custom color palette generated via Paletton.

70% match

Cola

This example visualizes the syntactic structure of a sentence as a network of nodes and links grouped into semantic layers, including the core predicate, referents, and peripheral elements. It uses WebCola for constraint-based layout and D3 v4 for rendering, with both SVG and canvas. The graph is built from a JSON file containing screen model data, and the layout organizes nodes into colored groups representing core and clause-level periphery.

69% match

Fork of WebCola Small Groups!

This fork of WebCola's Small Groups example visualizes sentence structure as a force-directed graph of clauses, predicates, and referents. Nodes are grouped by syntactic role, with colors distinguishing predicates, referents, and peripheries. The implementation uses the WebCola layout engine through its `d3adaptor`, with drag-and-drop interaction for repositioning nodes and double-clicking to release them. Data originates from a static JSON file containing the sentence "The shark bit the surfer savagely at the beach yesterday because it was hungry."