Triple

T16972391
Position Surface form Disambiguated ID Type / Status
Subject Han Meilin E411718 entity
Predicate givenName P17 FINISHED
Object Meilin E892932 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: Meilin | Statement: [Han Meilin, givenName, Meilin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Meilin
Context triple: [Han Meilin, givenName, Meilin]
  • A. Meilin chosen
    Meilin is the 13-year-old Chinese-Canadian protagonist of Pixar's animated film "Turning Red," who transforms into a giant red panda whenever her emotions run high.
  • B. Mingze
    Mingze is the given name of Xi Jinping’s daughter, Xi Mingze, who is known for maintaining a very private life despite her father’s prominent political role in China.
  • C. Jinyu
    Jinyu is a major variety of the Jin group of Chinese dialects spoken primarily in northern China, especially in Shanxi and surrounding regions.
  • D. Weida
    Weida is a river in eastern Germany that serves as a significant tributary of the Weiße Elster.
  • E. Heqing
    Heqing was an era name used during the Northern Qi dynasty in imperial China to designate a specific reign period.
  • 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_69d886ca8f348190812768ea8d5055ce completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3d0ae47f08190a13e98d20aba7f16 completed April 18, 2026, 6:42 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00d471d4248190acf40b6c11926a65 completed May 10, 2026, 6:54 p.m.
Created at: April 10, 2026, 5:31 a.m.