Triple

T54025
Position Surface form Disambiguated ID Type / Status
Subject HTTP/1.0 E1064 entity
Predicate successorOf P78 FINISHED
Object HTTP/0.9 E1064 NE FINISHED

How this triple was built (2 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: HTTP/0.9 | Statement: [HTTP/1.0, successorOf, HTTP/0.9]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: HTTP/0.9
Context triple: [HTTP/1.0, successorOf, HTTP/0.9]
  • A. HTTP chosen
    HTTP (Hypertext Transfer Protocol) is the foundational application-layer protocol used for transmitting web pages and other resources across the World Wide Web.
  • B. World Wide Web
    The World Wide Web is a global system of interlinked hypertext documents and resources accessed via the internet, enabling users worldwide to browse, share, and interact with information through web browsers.
  • C. Xanadu hypertext system
    The Xanadu hypertext system is an early, visionary hypertext project conceived by Ted Nelson that aimed to create a universal, bidirectionally linked, non-destructive document publishing and versioning system.
  • D. ARPANET
    ARPANET was the pioneering packet-switching network developed in the late 1960s that became the technical foundation of the modern Internet.
  • E. HUP
    HUP is a major academic medical center in Philadelphia that serves as the flagship teaching hospital of the University of Pennsylvania's health system.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69a248adc5b48190aa8db9fb092fb28a completed Feb. 28, 2026, 1:45 a.m.
NER Named-entity recognition batch_69a24b04ef708190876686da9db1f04d completed Feb. 28, 2026, 1:55 a.m.
NED1 Entity disambiguation (via context triple) batch_69a255398bac81909c4ae9bba79f6c19 completed Feb. 28, 2026, 2:38 a.m.
Created at: Feb. 28, 2026, 1:50 a.m.