Triple

T15211149
Position Surface form Disambiguated ID Type / Status
Subject Underground E363516 entity
Predicate composer P1361 FINISHED
Object Laura Karpman E1064235 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: Laura Karpman | Statement: [Underground, composer, Laura Karpman]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Laura Karpman
Context triple: [Underground, composer, Laura Karpman]
  • A. Laura Karpman chosen
    Laura Karpman is an Emmy-winning American composer known for her innovative and genre-spanning scores for film, television, and video games.
  • B. Fern Kraemer
    Fern Kraemer was a party to the landmark U.S. Supreme Court case Shelley v. Kraemer, which held that courts could not enforce racially restrictive housing covenants.
  • C. Linda Gottlieb
    Linda Gottlieb is an American film and television producer best known for producing the iconic 1987 romantic drama film "Dirty Dancing."
  • D. Joanne Larson
    Joanne Larson is a person known primarily as a relative of Claudia Larson, though specific public details about her life and work are not widely documented.
  • E. Renee Luskin
    Renee Luskin is a philanthropist and benefactor whose support and contributions led to the naming of UCLA’s Luskin School of Public Affairs in her honor.
  • 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_69d85a0b78bc8190b6e5ad51a2c4cfc5 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e0076ad4ec81908d36f541fca08d72 completed April 15, 2026, 9:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69fedd2f86688190bafdfe72033eda90 completed May 9, 2026, 7:07 a.m.
Created at: April 10, 2026, 3:11 a.m.