Triple

T6622030
Position Surface form Disambiguated ID Type / Status
Subject Ivan Chermayeff E149695 entity
Predicate designed P184 FINISHED
Object Mobil wordmark E88383 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: Mobil wordmark | Statement: [Ivan Chermayeff, designed, Mobil wordmark]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mobil wordmark
Context triple: [Ivan Chermayeff, designed, Mobil wordmark]
  • A. Mobil chosen
    Mobil is a major American oil company and fuel brand that became part of ExxonMobil after a 1999 merger.
  • B. Dior wordmark
    The Dior wordmark is the iconic, minimalist typographic logo that represents the French luxury fashion house Christian Dior across its products and branding.
  • C. Bernmobil
    Bernmobil is the public transport company responsible for operating trams, buses, and other urban transit services in the Swiss city of Bern.
  • D. Marken
    Marken is a small, picturesque former island village in the Netherlands known for its traditional wooden houses, fishing heritage, and distinctive cultural character.
  • E. Monogram
    Monogram is a famous mixed-media artwork by Robert Rauschenberg featuring a taxidermied goat encircled by a tire, emblematic of his groundbreaking “combine” paintings that merge painting and sculpture.
  • 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_69c687ed8a9c81908bb671717cb192ef completed March 27, 2026, 1:36 p.m.
NER Named-entity recognition batch_69c6af7ccaa481908b383b4fd671fa78 completed March 27, 2026, 4:25 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6e448b00081908b336a2bd7fb3820 completed March 27, 2026, 8:10 p.m.
Created at: March 27, 2026, 1:58 p.m.