Triple

T10170640
Position Surface form Disambiguated ID Type / Status
Subject Sioux Falls metropolitan area E235321 entity
Predicate containsCommunity P8617 FINISHED
Object Tea E770687 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: Tea | Statement: [Sioux Falls metropolitan area, containsCommunity, Tea]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tea
Context triple: [Sioux Falls metropolitan area, containsCommunity, Tea]
  • A. Tea chosen
    Tea is a widely consumed beverage made by steeping processed leaves of the Camellia sinensis plant in hot water, known for its variety of flavors, caffeine content, and cultural significance worldwide.
  • B. Chai
    Chai is a popular JavaScript assertion library commonly used in testing frameworks like Mocha to provide expressive, readable test assertions.
  • C. The Tea
    The Tea is an 1880 oil painting by American Impressionist Mary Cassatt that depicts two women in a refined domestic interior, exemplifying her focus on the private lives of women.
  • D. Green Tea
    "Green Tea" is a gothic short story by Sheridan Le Fanu that follows a clergyman haunted by a demonic monkey, exploring themes of madness, the supernatural, and psychological terror.
  • E. TEA
    TEA is the state government agency responsible for overseeing public primary and secondary education in Texas.
  • 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_69ca84ceafd0819085828600e11bed6b completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cdec9d36608190be78665cc3410cf2 completed April 2, 2026, 4:12 a.m.
NED1 Entity disambiguation (via context triple) batch_69d300f7aafc8190be874efc755bd188 completed April 6, 2026, 12:40 a.m.
Created at: March 30, 2026, 9:10 p.m.