Triple

T4517444
Position Surface form Disambiguated ID Type / Status
Subject Mr. Big – Dr. Kananga E103185 entity
Predicate baseOfOperations P2591 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: [Mr. Big – Dr. Kananga, baseOfOperations, New York City]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: New York City
Context triple: [Mr. Big – Dr. Kananga, baseOfOperations, 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_69bd43dba59881908cf59b31df8c7ae1 completed March 20, 2026, 12:55 p.m.
NER Named-entity recognition batch_69bd572933408190b67c4ef6a7babe75 completed March 20, 2026, 2:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69bdacc411808190a80e0d6355c1cc60 completed March 20, 2026, 8:23 p.m.
Created at: March 20, 2026, 1:02 p.m.