[{"data":1,"prerenderedAt":483},["ShallowReactive",2],{"doc-\u002Fdocs\u002Fcore-concepts\u002Fterminology-graph-explorer":3,"docs-nav":359},{"id":4,"title":5,"body":6,"description":351,"extension":352,"meta":353,"navigation":354,"path":355,"seo":356,"stem":357,"__hash__":358},"content\u002Fdocs\u002F2.core-concepts\u002F7.terminology-graph-explorer.md","Terminology Graph Explorer",{"type":7,"value":8,"toc":337},"minimark",[9,13,21,32,39,44,55,62,66,73,76,101,112,115,121,125,132,153,156,160,167,173,180,183,214,218,224,247,253,268,272,278,293,297,304,308,324,328],[10,11,5],"h1",{"id":12},"terminology-graph-explorer",[14,15,16,17,20],"p",{},"The ",[18,19,5],"strong",{}," is an interactive map of the domain-specific terminology inside a knowledge base. It shows which concepts appear across your documents and how they co-occur — which pairs of terms tend to be discussed together, and how strongly.",[14,22,23,24,27,28,31],{},"The graph is useful in two distinct ways: as a ",[18,25,26],{},"research tool"," you can use directly to navigate your corpus from a concept perspective, and as a ",[18,29,30],{},"foundation"," the agent draws on when it needs to understand what a term means in your specific domain.",[14,33,34],{},[35,36],"img",{"alt":37,"src":38},"Terminology Graph Explorer Screenshot, showing an edge selected between two nodes and the passage that connects them","\u002Fdocs\u002Fcore-concepts\u002Fterminology-graph-explorer.webp",[40,41,43],"h2",{"id":42},"what-the-graph-represents","What the graph represents",[14,45,46,47,50,51,54],{},"Each ",[18,48,49],{},"node"," is a term extracted from your documents — a concept, method, entity, or phrase that appears enough times to be meaningful. The connections between nodes are ",[18,52,53],{},"co-occurrence edges",": two terms are connected if they appear in the same semantic chunk across your corpus. The thicker an edge, the more papers in which those two terms appear together in a single semantically cohesive chunk.",[14,56,57,58,61],{},"Nodes are sized by the number of chunks they appear in, and the ",[18,59,60],{},"information score"," (shown in the info sidebar) reflects how information-rich the passages containing that term tend to be regarding the term — a high score means the term is substantively discussed.",[40,63,65],{"id":64},"building-the-graph","Building the graph",[14,67,68,69,72],{},"The terminology graph is built per knowledge base, not per project. It requires ",[18,70,71],{},"at least 10 documents"," to be indexed in the KB before it can be built.",[14,74,75],{},"To build or rebuild it:",[77,78,79,87,94],"ol",{},[80,81,82,83,86],"li",{},"Open the KB from the ",[18,84,85],{},"Knowledge Bases"," view.",[80,88,89,90,93],{},"Scroll to the ",[18,91,92],{},"Terminology Graph"," section at the bottom of the KB page.",[80,95,96,97,100],{},"Click ",[18,98,99],{},"Rebuild",".",[14,102,103,104,107,108,111],{},"Building the graph is free of charge and runs in the background. You can watch the progress bar fill from 0% to 100%. Once it reaches ",[18,105,106],{},"Completed",", the ",[18,109,110],{},"Explore"," button becomes available.",[14,113,114],{},"Rebuilds are throttled: once a build completes, you can trigger a new rebuild after four hours.",[14,116,117],{},[35,118],{"alt":119,"src":120},"Terminology Graph Section Secreenshot","\u002Fdocs\u002Fcore-concepts\u002Fui-terminology-graph-section.webp",[40,122,124],{"id":123},"the-graph-view","The graph view",[14,126,127,128,131],{},"The graph shows a local neighbourhood around a ",[18,129,130],{},"root term"," — not the entire graph at once, which would be too dense to navigate. From a root, you see:",[133,134,135,141,147],"ul",{},[80,136,137,140],{},[18,138,139],{},"Root node"," — the term you navigated to, displayed in a dark node at the centre.",[80,142,143,146],{},[18,144,145],{},"First-hop neighbours"," — terms that directly co-occur with the root, shown in a blue-tinted ring around it.",[80,148,149,152],{},[18,150,151],{},"Second-hop neighbours"," — terms one step further out, shown in a lighter colour.",[14,154,155],{},"Edges are drawn as curves between nodes. Edge thickness scales with the number of papers in which the two terms co-occur in at least one semantic chunk.",[40,157,159],{"id":158},"searching-and-navigating","Searching and navigating",[14,161,162,163,166],{},"Use the ",[18,164,165],{},"search box"," in the top bar to jump to any term. As you type, autocomplete suggestions appear, showing the term's name alongside its paper count and chunk count. Select a suggestion to navigate there — that term becomes the new root and the graph redraws around it.",[14,168,169,172],{},[18,170,171],{},"Double-clicking any node"," also navigates to it, making that node the new root. This is the primary way to move through the graph by following concept chains.",[14,174,175,176,179],{},"The explorer maintains a ",[18,177,178],{},"navigation history",". If you navigated through several terms, you can go back and forward using the browser back\u002Fforward buttons.",[14,181,182],{},"Keyboard shortcuts also work when the search box is not focused:",[133,184,185,198,206],{},[80,186,187,197],{},[18,188,189,193,194],{},[190,191,192],"code",{},"+"," \u002F ",[190,195,196],{},"="," — zoom in",[80,199,200,205],{},[18,201,202],{},[190,203,204],{},"-"," — zoom out",[80,207,208,213],{},[18,209,210],{},[190,211,212],{},"z"," — zoom to the currently selected node",[40,215,217],{"id":216},"inspecting-nodes-and-edges","Inspecting nodes and edges",[14,219,220,223],{},[18,221,222],{},"Click a node"," to select it. The Info tab on the right sidebar shows:",[133,225,226,229,235,241],{},[80,227,228],{},"The term's display form",[80,230,231,234],{},[18,232,233],{},"Papers"," — number of documents in which this term appears",[80,236,237,240],{},[18,238,239],{},"Chunks"," — number of semantic chunks containing this term",[80,242,243,246],{},[18,244,245],{},"Info score"," — average information density regarding this term in passages containing it. A higher score means the term is discussed in more substantive contexts.",[14,248,249,252],{},[18,250,251],{},"Click an edge"," to select it. The Info tab on the right sidebar shows the co-occurrence relationship:",[133,254,255,258,263],{},[80,256,257],{},"Both term names",[80,259,260,262],{},[18,261,233],{}," — number of documents where both terms co-occur",[80,264,265,267],{},[18,266,239],{}," — number of chunks where both terms appear together",[40,269,271],{"id":270},"viewing-supporting-text","Viewing supporting text",[14,273,16,274,277],{},[18,275,276],{},"Chunks tab"," in the right sidebar shows the actual text passages from your documents that are associated with the current selection. Each entry is a citation card linking back to the source document at the exact passage — the same citation format used on mindmap nodes, similarly you can add labels to these citation items for quick reference.",[133,279,280,286],{},[80,281,282,283,285],{},"When a ",[18,284,49],{}," is selected: all passages containing that term, ranked by information score - the first entries are the most informative regarding that term.",[80,287,288,289,292],{},"When an ",[18,290,291],{},"edge"," is selected: passages where both terms appear together.",[40,294,296],{"id":295},"how-the-agent-uses-the-terminology-graph","How the agent uses the terminology graph",[14,298,299,300,303],{},"When the agent runs a research workflow, it doesn't just query your documents by keyword or embedding similarity. 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