Triple

T15566199
Position Surface form Disambiguated ID Type / Status
Subject Louis Dreyfus Company E371120 entity
Predicate competitor P1375 FINISHED
Object Archer Daniels Midland E366016 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: Archer Daniels Midland | Statement: [Louis Dreyfus Company, competitor, Archer Daniels Midland]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Archer Daniels Midland
Context triple: [Louis Dreyfus Company, competitor, Archer Daniels Midland]
  • A. Archer Daniels Midland chosen
    Archer Daniels Midland is a large American multinational food processing and commodities trading corporation.
  • B. Cargill
    Cargill is a large American privately held global food and agribusiness company involved in commodities trading, food production, and agricultural services.
  • C. Corn Products Refining Company
    Corn Products Refining Company was a major early 20th-century American agribusiness firm specializing in processing corn into starches, sweeteners, and other industrial and food products.
  • D. Bunge
    Bunge is the unicameral legislative body and main law-making institution of the United Republic of Tanzania.
  • E. Bunge
    Bunge is a surname most notably associated with Nikolai Bunge, a prominent 19th-century Russian economist and statesman.
  • 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_69d85cc6cf40819091f4a5facee1ebe6 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e04ddd753c8190b51eaef433258081 completed April 16, 2026, 2:47 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff456a3b08819092f9f517bbef5577 completed May 9, 2026, 2:32 p.m.
Created at: April 10, 2026, 4:10 a.m.