Triple

T14875311
Position Surface form Disambiguated ID Type / Status
Subject Financial District, Hyderabad E349851 entity
Predicate hasCompany P1287 FINISHED
Object Deloitte E482358 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: Deloitte | Statement: [Financial District, Hyderabad, hasCompany, Deloitte]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Deloitte
Context triple: [Financial District, Hyderabad, hasCompany, Deloitte]
  • A. Deloitte chosen
    Deloitte is one of the world’s largest professional services firms, providing audit, consulting, tax, and advisory services to clients globally.
  • B. Ernst & Young
    Ernst & Young is a global professional services firm, known as one of the "Big Four" accounting organizations, providing audit, tax, consulting, and advisory services to clients worldwide.
  • C. PricewaterhouseCoopers
    PricewaterhouseCoopers (PwC) is one of the world’s largest professional services networks, providing audit, tax, and consulting services to clients across a wide range of industries.
  • D. KPMG
    KPMG is one of the world’s largest professional services firms, providing audit, tax, and advisory services to clients across a wide range of industries.
  • E. Accenture
    Accenture is a global professional services company specializing in consulting, technology, and outsourcing solutions for businesses and governments worldwide.
  • 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_69d822ee4f408190b6ac3b2fa434f0df completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69ded5e3e5d48190a132f2cf012b01e2 completed April 15, 2026, 12:03 a.m.
NED1 Entity disambiguation (via context triple) batch_69fe6b52c12481908d0173a2a3ed854b completed May 8, 2026, 11:01 p.m.
Created at: April 10, 2026, 1:55 a.m.