Triple

T22023270
Position Surface form Disambiguated ID Type / Status
Subject Blood and Water E543893 entity
Predicate mainCharacter P1183 FINISHED
Object Joanna Han 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: Joanna Han | Statement: [Blood and Water, mainCharacter, Joanna Han]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Joanna Han
Context triple: [Blood and Water, mainCharacter, Joanna Han]
  • A. Joanna Han chosen
    Joanna Han is a character in the Canadian teen drama series "Blood and Water," which follows the lives and secrets of a wealthy Chinese-Canadian family.
  • B. Joanna Hanley
    Joanna Hanley is the ambitious big-city lawyer protagonist of the Canadian legal drama series "Burden of Truth."
  • C. Sandra Kim
    Sandra Kim is a Belgian singer best known for winning the Eurovision Song Contest in 1986 at the age of 13, making her the youngest ever winner.
  • D. Joanna Holland
    Joanna Holland is an American former model best known as the third wife of television host Johnny Carson.
  • E. Liz Hannah
    Liz Hannah is an American screenwriter and producer best known for co-writing the acclaimed historical drama film "The Post."
  • 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_69e11e2e8ea4819084210fe06d3a1b8d completed April 16, 2026, 5:36 p.m.
NER Named-entity recognition batch_69f127c9959481908da6bed356199f75 completed April 28, 2026, 9:34 p.m.
Created at: April 16, 2026, 8:23 p.m.