Triple

T14452399
Position Surface form Disambiguated ID Type / Status
Subject Adani Group E358367 entity
Predicate listedUnit P114335 FINISHED
Object Adani Wilmar E1101442 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: Adani Wilmar | Statement: [Adani Group, listedUnit, Adani Wilmar]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Adani Wilmar
Context triple: [Adani Group, listedUnit, Adani Wilmar]
  • A. Adani Wilmar chosen
    Adani Wilmar is an Indian fast-moving consumer goods company best known for its edible oils and food products sold under brands like Fortune.
  • B. Adani Enterprises
    Adani Enterprises is the flagship publicly listed company of the Adani Group, engaged in diverse businesses including energy, infrastructure, and mining in India and abroad.
  • C. Adani Group
    Adani Group is a major Indian multinational conglomerate with diversified interests in ports, logistics, energy, and infrastructure.
  • D. Godrej Agrovet Limited
    Godrej Agrovet Limited is an Indian agribusiness company engaged in animal feed, crop protection, dairy, and related agricultural products and services.
  • E. Wadia Group
    Wadia Group is one of India’s oldest conglomerates, with diversified interests spanning textiles, aviation, real estate, food, and chemicals.
  • 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_69d82794dfa081909b9134ad2e32244b completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de916244948190bb09d1bfc485ba50 completed April 14, 2026, 7:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd6d86dbc0819085fef8fa8b45b373 completed May 8, 2026, 4:58 a.m.
Created at: April 10, 2026, 1:19 a.m.