Triple

T8725728
Position Surface form Disambiguated ID Type / Status
Subject Monica Raymund E207125 entity
Predicate hasResidence P75 FINISHED
Object New York City E40 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: New York City | Statement: [Monica Raymund, hasResidence, New York City]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: New York City
Context triple: [Monica Raymund, hasResidence, New York City]
  • A. New York City chosen
    New York City is the largest city in the United States, a global center of finance, culture, media, and technology.
  • B. NYC
    NYC is a historic American railroad company that operated major passenger and freight services across the northeastern and midwestern United States.
  • C. New York
    New York is a populous and economically significant U.S. state known for New York City, a global center of finance, culture, and media.
  • D. 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.
  • E. Manhattan
    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.
  • 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_69ca835811d8819081ea00fd2a2c9a1c completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc5d158b0481908249610458f97306 completed March 31, 2026, 11:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69cf27abf324819098bd6ecfd5a4d8cc completed April 3, 2026, 2:36 a.m.
Created at: March 30, 2026, 6:36 p.m.