Triple

T19534293
Position Surface form Disambiguated ID Type / Status
Subject Yourself or Someone Like You E488729 entity
Predicate hasPart P35 FINISHED
Object Damn 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: Damn | Statement: [Yourself or Someone Like You, hasPart, Damn]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Damn
Context triple: [Yourself or Someone Like You, hasPart, Damn]
  • A. Damn chosen
    "Damn" is a popular Afrobeats song by Nigerian singer Omah Lay, known for its mellow vibe, introspective lyrics, and fusion of Afro-fusion and R&B elements.
  • B. Damn
    Damn is a critically acclaimed 2017 studio album by American rapper Kendrick Lamar that blends introspective lyricism with innovative production and won the Pulitzer Prize for Music.
  • C. Damn!
    "Damn!" is a 2003 crunk/hip-hop single by YoungBloodZ featuring Lil Jon, best known for its aggressive energy and memorable hook that made it a club and radio hit.
  • D. Dammit
    "Dammit" is a fast-paced pop-punk song by Blink-182, widely recognized as one of their breakout hits from the late 1990s.
  • E. Damnation
    Damnation is a 1988 Hungarian black-and-white art film directed by Béla Tarr, known for its bleak atmosphere, long takes, and exploration of existential despair in a decaying industrial town.
  • 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_69d8e8db5b6c8190984b61f91981f575 completed April 10, 2026, 12:11 p.m.
NER Named-entity recognition batch_69e636417ed88190b4c66a323bca776f completed April 20, 2026, 2:20 p.m.
Created at: April 10, 2026, 1:41 p.m.