Triple

T2198914
Position Surface form Disambiguated ID Type / Status
Subject New York World's Fair E50441 entity
Predicate notableExhibitor P28143 FINISHED
Object AT&T E89783 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: AT&T | Statement: [New York World's Fair, notableExhibitor, AT&T]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: AT&T
Context triple: [New York World's Fair, notableExhibitor, AT&T]
  • A. AT&T chosen
    AT&T is a major American telecommunications conglomerate known for providing wireless, internet, and media services nationwide.
  • B. Verizon
    Verizon is a major American telecommunications company providing wireless, internet, and related communication services across the United States and globally.
  • C. Ameritech
    Ameritech was a regional telecommunications company formed after the breakup of AT&T’s Bell System, serving the Midwestern United States with local and long-distance phone services.
  • D. Alltel
    Alltel was a major American wireless telecommunications company that provided mobile phone services across numerous U.S. states before being largely acquired by Verizon Wireless.
  • E. T-Mobile US
    T-Mobile US is a major American wireless network operator known for its nationwide mobile phone services and aggressive “Un-carrier” marketing strategy.
  • 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_69a88b044ab48190add007487680f009 completed March 4, 2026, 7:41 p.m.
NER Named-entity recognition batch_69abc5b101d48190a321625720d537b6 completed March 7, 2026, 6:29 a.m.
NED1 Entity disambiguation (via context triple) batch_69aef085c9f48190a9adfff98c30f4f5 completed March 9, 2026, 4:08 p.m.
Created at: March 4, 2026, 7:46 p.m.