Triple

T6582270
Position Surface form Disambiguated ID Type / Status
Subject Black Lines E157324 entity
Predicate titleInOriginalLanguage P13516 FINISHED
Object Schwarze Linien E157324 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: Schwarze Linien | Statement: [Black Lines, titleInOriginalLanguage, Schwarze Linien]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Schwarze Linien
Context triple: [Black Lines, titleInOriginalLanguage, Schwarze Linien]
  • A. Black Lines chosen
    Black Lines is an abstract painting by Wassily Kandinsky that exemplifies his pioneering use of bold linear forms and vibrant color to explore non-representational expression.
  • B. White Line
    "White Line" is a grungy, guitar-driven rock song by Neil Young and Crazy Horse from the 1990 album *Ragged Glory*.
  • C. Figures in Black
    Figures in Black is a critical work of literary and cultural analysis by Henry Louis Gates Jr. that explores Black representation, language, and identity in African American literature.
  • D. Blacker
    Blacker is a comparative form of the color term "black," indicating a greater degree of darkness or blackness.
  • E. Black and Blue
    "Black and Blue" is a bestselling novel by Anna Quindlen that explores domestic abuse and a woman's struggle to escape and rebuild her life.
  • 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_69c6882b3a108190b3a9eb343ae4162c completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6ae9238b481909278316ef195018d completed March 27, 2026, 4:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6d572c4708190844f4b1abee8ca86 completed March 27, 2026, 7:07 p.m.
Created at: March 27, 2026, 1:54 p.m.