Triple

T4599960
Position Surface form Disambiguated ID Type / Status
Subject Python scientific stack E100298 entity
Predicate hasComponent P35 FINISHED
Object NetworkX
NetworkX is a Python library for creating, analyzing, and visualizing complex networks and graphs.
 E459727 NE FINISHED

How this triple was built (4 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: NetworkX | Statement: [Python scientific stack, hasComponent, NetworkX]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: NetworkX
Context triple: [Python scientific stack, hasComponent, NetworkX]
  • A. DGL
    DGL is the vehicle registration code assigned to the town of Głogów in Poland.
  • B. Matplotlib
    Matplotlib is a widely used Python plotting library for creating static, animated, and interactive visualizations.
  • C. Seaborn
    Seaborn is a Python data visualization library built on top of Matplotlib that provides a high-level interface for creating attractive and informative statistical graphics.
  • D. Seaborn
    Seaborn is a masculine given name of English origin, historically used in colonial America and associated with individuals such as Seaborn Cotton.
  • E. Canvas Network
    Canvas Network is an online learning platform that hosts and delivers massive open online courses (MOOCs) from universities and institutions worldwide.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: NetworkX
Triple: [Python scientific stack, hasComponent, NetworkX]
Generated description
NetworkX is a Python library for creating, analyzing, and visualizing complex networks and graphs.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: NetworkX
Target entity description: NetworkX is a Python library for creating, analyzing, and visualizing complex networks and graphs.
  • A. DGL
    DGL is the vehicle registration code assigned to the town of Głogów in Poland.
  • B. Matplotlib
    Matplotlib is a widely used Python plotting library for creating static, animated, and interactive visualizations.
  • C. Seaborn
    Seaborn is a Python data visualization library built on top of Matplotlib that provides a high-level interface for creating attractive and informative statistical graphics.
  • D. Seaborn
    Seaborn is a masculine given name of English origin, historically used in colonial America and associated with individuals such as Seaborn Cotton.
  • E. Canvas Network
    Canvas Network is an online learning platform that hosts and delivers massive open online courses (MOOCs) from universities and institutions worldwide.
  • F. None of above. chosen

Provenance (5 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69bd43cbc014819098b45f435908f88a completed March 20, 2026, 12:55 p.m.
NER Named-entity recognition batch_69bd5971f448819090f6e76c7d3ffc2d completed March 20, 2026, 2:28 p.m.
NED1 Entity disambiguation (via context triple) batch_69bdfa54bb0c819081265a6d159ad790 completed March 21, 2026, 1:54 a.m.
NEDg Description generation batch_69bdfb37b1448190a4001b9ed2b79012 completed March 21, 2026, 1:58 a.m.
NED2 Entity disambiguation (via description) batch_69bdfc0e456c81908efa3858d981ccc0 completed March 21, 2026, 2:01 a.m.
Created at: March 20, 2026, 1:11 p.m.