Triple

T5964627
Position Surface form Disambiguated ID Type / Status
Subject React Router E132720 entity
Predicate hasVersion P455 FINISHED
Object v5
v5 is a major version of the React Router library that introduced a more declarative, component-based approach to routing in React applications.
 E559080 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: v5 | Statement: [React Router, hasVersion, v5]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: v5
Context triple: [React Router, hasVersion, v5]
  • A. VEX
    VEX is the commonly used acronym for Venus Express, a European Space Agency mission that studied the atmosphere and surface of Venus.
  • B. V4
    V4 is a regional alliance of four Central European countries—Czech Republic, Hungary, Poland, and Slovakia—cooperating on political, economic, and security issues within the European context.
  • C. V.
    V. is Thomas Pynchon's 1963 debut novel, a complex, postmodern work that interweaves multiple narratives and historical periods in a quest surrounding the mysterious figure or concept known only as "V."
  • D. U5
    U5 is one of the lines of the Frankfurt U-Bahn rapid transit system in Frankfurt, Germany.
  • E. U5
    U5 is a major line of the Berlin U-Bahn rapid transit system that runs east–west across the city, connecting central Berlin with several eastern districts.
  • 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: v5
Triple: [React Router, hasVersion, v5]
Generated description
v5 is a major version of the React Router library that introduced a more declarative, component-based approach to routing in React applications.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: v5
Target entity description: v5 is a major version of the React Router library that introduced a more declarative, component-based approach to routing in React applications.
  • A. VEX
    VEX is the commonly used acronym for Venus Express, a European Space Agency mission that studied the atmosphere and surface of Venus.
  • B. V4
    V4 is a regional alliance of four Central European countries—Czech Republic, Hungary, Poland, and Slovakia—cooperating on political, economic, and security issues within the European context.
  • C. V.
    V. is Thomas Pynchon's 1963 debut novel, a complex, postmodern work that interweaves multiple narratives and historical periods in a quest surrounding the mysterious figure or concept known only as "V."
  • D. U5
    U5 is one of the lines of the Frankfurt U-Bahn rapid transit system in Frankfurt, Germany.
  • E. U5
    U5 is a major line of the Berlin U-Bahn rapid transit system that runs east–west across the city, connecting central Berlin with several eastern districts.
  • 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_69c0086c2364819091e9fe2f58fa2517 completed March 22, 2026, 3:19 p.m.
NER Named-entity recognition batch_69c03a0240cc81909d7c75c7e6d630f7 completed March 22, 2026, 6:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69c0e3f32e8481908a6075684287c412 completed March 23, 2026, 6:55 a.m.
NEDg Description generation batch_69c0ebfa3a9c81908a183f995350366b completed March 23, 2026, 7:30 a.m.
NED2 Entity disambiguation (via description) batch_69c0ec61672c8190b98cead75cac84d5 completed March 23, 2026, 7:31 a.m.
Created at: March 22, 2026, 4:03 p.m.