Triple

T14065039
Position Surface form Disambiguated ID Type / Status
Subject Ben Haggerty E338444 entity
Predicate notableAlias P39 FINISHED
Object Professor Macklemore E119606 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: Professor Macklemore | Statement: [Ben Haggerty, notableAlias, Professor Macklemore]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Professor Macklemore
Context triple: [Ben Haggerty, notableAlias, Professor Macklemore]
  • A. Macklemore chosen
    Macklemore is an American rapper and songwriter from Seattle, best known for hits like "Thrift Shop" and "Can't Hold Us" and his collaborations with producer Ryan Lewis.
  • B. AJ McLean
    AJ McLean is an American singer and performer best known as one of the original members and lead vocalists of the pop group Backstreet Boys.
  • C. Jonathan Coulton
    Jonathan Coulton is an American singer-songwriter known for his witty, geek-culture-inspired songs and contributions to projects like the video game Portal and various stage and screen works.
  • D. Dean Sampson
    Dean Sampson is the arrogant, manipulative antagonist in the teen romantic comedy film "She's All That."
  • E. Mike Kellin
    Mike Kellin was an American character actor known for his prolific work in film, television, and theater from the 1950s through the 1970s.
  • 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_69d81c67ba6c819091935650dfb3b895 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de5689c7f48190a47ca94eaa8a9ef9 completed April 14, 2026, 3 p.m.
NED1 Entity disambiguation (via context triple) batch_69fcb669111081909ccd167f41571a00 completed May 7, 2026, 3:57 p.m.
Created at: April 9, 2026, 10:21 p.m.