Triple

T16365966
Position Surface form Disambiguated ID Type / Status
Subject Afrodeezia E397437 entity
Predicate hasPart P35 FINISHED
Object Water Dancer E117053 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: Water Dancer | Statement: [Afrodeezia, hasPart, Water Dancer]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Water Dancer
Context triple: [Afrodeezia, hasPart, Water Dancer]
  • A. The Water Dancer chosen
    The Water Dancer is a debut novel by Ta-Nehisi Coates that blends historical fiction and magical realism to explore slavery, memory, and freedom in the antebellum American South.
  • B. Sula
    Sula is a 1973 novel by American author Toni Morrison that explores Black female friendship, community, and identity in a small Ohio town.
  • C. Sula
    Sula is a coastal municipality in Møre og Romsdal county, Norway, known for its fishing industry, maritime heritage, and scenic island landscapes.
  • D. Sula
    Sula is a genus of large seabirds known as boobies, characterized by their strong diving ability and predominantly tropical oceanic distribution.
  • E. The Lowland
    The Lowland is a novel by Jhumpa Lahiri that explores the intertwined lives of two brothers from Calcutta against the backdrop of political upheaval and family tragedy.
  • 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_69d87f2778dc8190aa95c7572db127e6 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e2ff3c915c81909e1757fc31921876 completed April 18, 2026, 3:49 a.m.
NED1 Entity disambiguation (via context triple) batch_6a002dc0b3d4819089e6fba536ec8a11 completed May 10, 2026, 7:03 a.m.
Created at: April 10, 2026, 5:08 a.m.