Triple

T4331160
Position Surface form Disambiguated ID Type / Status
Subject New York Magazine E96750 entity
Predicate hasSection P35 FINISHED
Object Grub Street E430831 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: Grub Street | Statement: [New York Magazine, hasSection, Grub Street]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Grub Street
Context triple: [New York Magazine, hasSection, Grub Street]
  • A. Grub Street chosen
    Grub Street is a popular food and restaurant blog and section of New York Magazine known for its coverage of dining trends, chefs, and the culinary scene.
  • B. The Street
    The Street is a British television drama series known for its gritty, character-driven stories set in a working-class neighborhood.
  • C. Remedios Street
    Remedios Street is a notable road in the Malate district of Manila, Philippines, known for its nightlife, restaurants, and cultural landmarks.
  • D. Ward of Cornhill
    The Ward of Cornhill is one of the historic administrative and electoral divisions of the City of London, centered on the traditional commercial area around Cornhill.
  • E. Bleecker Street
    Bleecker Street is an American independent film distribution company known for releasing critically acclaimed arthouse and specialty films.
  • 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_69b34542fd908190b11b08faad8decfd completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b3514c39748190900e13e70ed8848c completed March 12, 2026, 11:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5db98ae888190aac5b5b7839ae7dd completed March 14, 2026, 10:05 p.m.
Created at: March 12, 2026, 11:13 p.m.