Triple

T13858588
Position Surface form Disambiguated ID Type / Status
Subject NYC Media E333127 entity
Predicate hasChannel P8080 FINISHED
Object NYC Life E333128 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: NYC Life | Statement: [NYC Media, hasChannel, NYC Life]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: NYC Life
Context triple: [NYC Media, hasChannel, NYC Life]
  • A. NYC Life chosen
    NYC Life is a New York City-based television channel that focuses on local culture, lifestyle, and city-centric programming.
  • B. New Yorkers
    New Yorkers is a collection of short stories by Bai Xianyong that portrays the lives and emotional struggles of Chinese immigrants and expatriates in New York City.
  • C. NYC
    NYC is a historic American railroad company that operated major passenger and freight services across the northeastern and midwestern United States.
  • D. NYCT
    NYCT is the primary bus operating division of New York City's Metropolitan Transportation Authority, running most of the city's local and express bus services.
  • E. New York Scenes
    New York Scenes is a section of Jack Kerouac’s travelogue "Lonesome Traveler" that captures his impressions and experiences of life in New York City.
  • 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_69d81c5ba13c8190839315f54768acfd completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de02de38e48190b6ead95561031c32 completed April 14, 2026, 9:03 a.m.
NED1 Entity disambiguation (via context triple) batch_69f7c0fd3ffc8190965a730843411b80 completed May 3, 2026, 9:41 p.m.
Created at: April 9, 2026, 10:14 p.m.