Triple

T21863845
Position Surface form Disambiguated ID Type / Status
Subject Love All, Serve All E539833 entity
Predicate associatedWithBrand P2830 FINISHED
Object Hard Rock 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: Hard Rock | Statement: [Love All, Serve All, associatedWithBrand, Hard Rock]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hard Rock
Context triple: [Love All, Serve All, associatedWithBrand, Hard Rock]
  • A. Hard Rock chosen
    Hard Rock is a globally recognized entertainment and hospitality brand known for its rock-and-roll–themed restaurants, hotels, casinos, and music memorabilia.
  • B. Rock
    "Rock" is a popular Afrobeats/hip-hop song by Nigerian rapper and singer Olamide, known for its smooth melody and romantic lyrics.
  • C. Rock
    Rock is the original civilian name of Mega Man, the humanoid robot protagonist of Capcom’s classic action-platformer video game series.
  • D. Rock
    Rock is a professional box lacrosse team based in Toronto, Ontario, competing in the National Lacrosse League.
  • E. Rock
    Rock is a small, affluent coastal village in Cornwall, England, known for its sailing, watersports, and popularity as a holiday destination.
  • 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_69e0c478f59081909d54302b57fc1ce3 completed April 16, 2026, 11:14 a.m.
NER Named-entity recognition batch_69f0d63d927c8190bcfccc140357484c completed April 28, 2026, 3:46 p.m.
Created at: April 16, 2026, 6:56 p.m.