Triple

T16938279
Position Surface form Disambiguated ID Type / Status
Subject Kimmy Schmidt E410880 entity
Predicate setting P1957 FINISHED
Object Manhattan E8787 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: Manhattan | Statement: [Kimmy Schmidt, setting, Manhattan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Manhattan
Context triple: [Kimmy Schmidt, setting, Manhattan]
  • A. Manhattan chosen
    Manhattan is the densely populated, iconic core borough of New York City, known for its skyscrapers, cultural institutions, and role as a global financial and media center.
  • B. Manhattan
    The Manhattan is a classic whiskey-based cocktail, traditionally made with rye or bourbon, sweet vermouth, and bitters, and typically served stirred and garnished with a cherry.
  • C. Manhattan
    Manhattan is a village in Will County, Illinois, known as a growing suburban community southwest of Chicago.
  • D. New York City
    New York City is the largest city in the United States, a global center of finance, culture, media, and technology.
  • E. NYC
    NYC is a historic American railroad company that operated major passenger and freight services across the northeastern and midwestern United States.
  • 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_69d886c886688190967be07322597ac9 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3cf2b88bc8190aeb7b07032478ae3 completed April 18, 2026, 6:36 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00cfc0dcd081909f715e0f2aad67c7 completed May 10, 2026, 6:34 p.m.
Created at: April 10, 2026, 5:30 a.m.