Triple

T13776369
Position Surface form Disambiguated ID Type / Status
Subject Diane Chambers E331016 entity
Predicate associatedWith P37 FINISHED
Object Rebecca Howe E375429 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: Rebecca Howe | Statement: [Diane Chambers, associatedWith, Rebecca Howe]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rebecca Howe
Context triple: [Diane Chambers, associatedWith, Rebecca Howe]
  • A. Rebecca Howe chosen
    Rebecca Howe is a fictional character on the sitcom "Cheers," known as the ambitious and often neurotic bar manager who replaces Diane Chambers.
  • B. Rebecca Lovell
    Rebecca Lovell is an American musician best known as the vocalist and multi-instrumentalist of the roots-rock duo Larkin Poe.
  • C. Rebecca Lane
    Rebecca Lane is a central character in the science fiction horror film "The Last Days on Mars," serving as one of the astronauts confronting a deadly infection on the Martian surface.
  • D. Rebecca Garland
    Rebecca Garland is one of the children of Merrick Garland, the U.S. Attorney General and former federal judge.
  • E. Rebecca Calhoun
    Rebecca Calhoun was the wife of American Revolutionary War general and South Carolina politician Andrew Pickens.
  • 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_69d81c583b0081909e408a17db517a21 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de0238bdbc8190a946e6e5431632a5 completed April 14, 2026, 9 a.m.
NED1 Entity disambiguation (via context triple) batch_69fd8a9c41908190b789765861bd9924 completed May 8, 2026, 7:02 a.m.
Created at: April 9, 2026, 10:10 p.m.