Triple

T3847572
Position Surface form Disambiguated ID Type / Status
Subject Li Ning E85209 entity
Predicate givenName P17 FINISHED
Object Ning E47371 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: Ning | Statement: [Li Ning, givenName, Ning]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ning
Context triple: [Li Ning, givenName, Ning]
  • A. Ning chosen
    Ning is an online platform that enables users and organizations to create their own custom social networks and communities.
  • B. Xanga
    Xanga is a now largely defunct early 2000s social networking and blogging platform that allowed users to create personal blogs, share posts, and interact through comments and subscriptions.
  • C. Friendster
    Friendster was one of the earliest major social networking websites, popular in the early 2000s for connecting friends online before eventually declining and shutting down.
  • D. Plumtree
    Plumtree is a small border town in southwestern Zimbabwe that serves as a key road and rail gateway between Zimbabwe and Botswana.
  • E. Tumblr
    Tumblr is a microblogging and social networking platform known for its highly customizable blogs, fandom communities, and viral multimedia content.
  • 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_69aed936de1c81908f91bed80f70abb2 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aeebcb069881909d3536b18b7802a7 completed March 9, 2026, 3:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69b50414acdc81909bf0b62afa3fe536 completed March 14, 2026, 6:45 a.m.
Created at: March 9, 2026, 3:18 p.m.