Triple

T8764217
Position Surface form Disambiguated ID Type / Status
Subject Frank Ocean E208288 entity
Predicate secondStudioAlbum P6981 FINISHED
Object Blonde E755506 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: Blonde | Statement: [Frank Ocean, secondStudioAlbum, Blonde]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Blonde
Context triple: [Frank Ocean, secondStudioAlbum, Blonde]
  • A. Blonde
    Blonde is a 2007 pop album by French singer Alizée that marked a stylistic evolution in her music career.
  • B. Blonde
    Blonde is a 2022 psychological drama film written and directed by Andrew Dominik, loosely adapting Joyce Carol Oates’s novel to present a fictionalized, impressionistic portrayal of Marilyn Monroe’s life and career.
  • C. Blonde chosen
    Blonde is Frank Ocean’s critically acclaimed 2016 studio album that blends R&B, avant-pop, and introspective songwriting.
  • D. Blonde (novel)
    Blonde is a 2000 biographical novel by Joyce Carol Oates that offers a fictionalized, psychologically rich reimagining of the life and inner world of Marilyn Monroe.
  • E. The Blonde
    The Blonde is a character typically portrayed as an attractive, enigmatic woman whose appearance and demeanor often play into themes of allure and mystery.
  • 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_69ca835df7e08190ac875664cca8f9ca completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc5dfdef9881908a7f079d87e8e338 completed March 31, 2026, 11:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69cf5197263881908038b5e2105e9170 completed April 3, 2026, 5:35 a.m.
Created at: March 30, 2026, 6:40 p.m.