Triple

T3476907
Position Surface form Disambiguated ID Type / Status
Subject Coloring Book E73396 entity
Predicate hasPart P35 FINISHED
Object Blessings E203110 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: Blessings | Statement: [Coloring Book, hasPart, Blessings]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Blessings
Context triple: [Coloring Book, hasPart, Blessings]
  • A. Blessings chosen
    "Blessings" is a hip-hop single by Big Sean featuring Drake and Kanye West, known for its introspective lyrics about success, gratitude, and the pressures of fame.
  • B. So Blessed
    "So Blessed" is a song featured on the album "Emotions."
  • C. Saying Grace
    "Saying Grace" is a famous 1951 painting by American illustrator Norman Rockwell depicting a grandmother and young boy praying over a meal in a busy diner, celebrated for its warm, narrative portrayal of everyday American life.
  • D. Eighteen Benedictions
    The Eighteen Benedictions is a central Jewish prayer consisting of a series of blessings recited in the daily Amidah service.
  • E. Bless the Woman
    Bless the Woman is a Russian drama film best known for its portrayal of a woman's life and sacrifices across turbulent decades of Soviet history.
  • 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_69ad85b3c9b08190857cae74c7f36da9 completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adbb5a5cb88190be5624ae224e4c91 completed March 8, 2026, 6:09 p.m.
NED1 Entity disambiguation (via context triple) batch_69b3681586788190ade529f584b76396 completed March 13, 2026, 1:27 a.m.
Created at: March 8, 2026, 3:17 p.m.