Triple

T17573659
Position Surface form Disambiguated ID Type / Status
Subject Anxi County E428002 entity
Predicate hasProduct P3585 FINISHED
Object Tieguanyin oolong tea NE NERFINISHED

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: Tieguanyin oolong tea | Statement: [Anxi County, hasProduct, Tieguanyin oolong tea]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tieguanyin oolong tea
Context triple: [Anxi County, hasProduct, Tieguanyin oolong tea]
  • A. Tieguanyin tea chosen
    Tieguanyin tea is a famous Chinese oolong tea variety renowned for its floral aroma, rich flavor, and origins in Fujian Province.
  • B. Da Hong Pao
    Da Hong Pao is a legendary and highly prized Chinese oolong tea, renowned for its rich, roasted flavor and origin in the rocky cliffs of the Wuyi Mountains.
  • C. Keemun black tea
    Keemun black tea is a renowned Chinese black tea variety prized for its rich, mellow flavor and aromatic, winey notes.
  • D. Kangra tea
    Kangra tea is a distinctive variety of Indian tea from the Himalayan region of Himachal Pradesh, prized for its delicate flavor and aromatic quality.
  • E. Longjing tea
    Longjing tea is a famous high-quality Chinese green tea, renowned for its flat, jade-green leaves and delicate, nutty flavor, traditionally produced near Hangzhou in Zhejiang province.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d889e0385081908a04b66f4dd4bd0d completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e459330c788190907a02fc98e0e24b completed April 19, 2026, 4:25 a.m.
Created at: April 10, 2026, 5:50 a.m.