Triple

T11909798
Position Surface form Disambiguated ID Type / Status
Subject Nadine Chahine E283362 entity
Predicate employer P7 FINISHED
Object Monotype Imaging E283356 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: Monotype Imaging | Statement: [Nadine Chahine, employer, Monotype Imaging]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Monotype Imaging
Context triple: [Nadine Chahine, employer, Monotype Imaging]
  • A. Monotype chosen
    Monotype is a historic British type foundry and typesetting company renowned for producing and distributing classic typefaces used in print and digital media worldwide.
  • B. Aldus Corporation
    Aldus Corporation was a pioneering desktop publishing software company best known for creating PageMaker and helping popularize graphical user interfaces in publishing.
  • C. Corel Corporation
    Corel Corporation is a Canadian software company best known for products like CorelDRAW and WordPerfect.
  • D. Adobe Inc.
    Adobe Inc. is a multinational software company best known for its creative and multimedia products such as Photoshop, Illustrator, and Acrobat, widely used in digital media and design industries.
  • E. Linotype
    Linotype is a historic type foundry and former typesetting machine manufacturer known for revolutionizing printing technology and later for developing and distributing digital typefaces.
  • 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_69d6ab2c07e88190ba13b0d21fd6cf33 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d8e5278eb081909a7ecfe38beeeda9 completed April 10, 2026, 11:55 a.m.
NED1 Entity disambiguation (via context triple) batch_69f49ce47d488190af7f832e7719a4ce completed May 1, 2026, 12:30 p.m.
Created at: April 8, 2026, 9:44 p.m.