Triple

T22347270
Position Surface form Disambiguated ID Type / Status
Subject Charles-Louis Havas E552425 entity
Predicate founded P104 FINISHED
Object Agence Havas NE NERFINISHED

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: Agence Havas | Statement: [Charles-Louis Havas, founded, Agence Havas]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Agence Havas
Context triple: [Charles-Louis Havas, founded, Agence Havas]
  • A. Havas
    Havas is a major global advertising and communications group headquartered in France, known for its extensive network of creative, media, and marketing agencies.
  • B. Havas Agency chosen
    Havas Agency was a major French advertising and communications firm that evolved from one of the world’s oldest news agencies into a global marketing and media network.
  • C. J. Walter Thompson Worldwide
    J. Walter Thompson Worldwide is one of the oldest and most influential global advertising agencies, known for pioneering many modern advertising practices and campaigns.
  • D. J. Walter Thompson
    J. Walter Thompson is one of the world's oldest and most influential advertising agencies, known for pioneering modern advertising practices and global brand campaigns.
  • E. Walter Thompson
    Walter Thompson is an editor known for his work on the film "Pitfall."
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e11e4a0ad08190a385b4d343cf6524 completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f157995bec819080b8d05fa88704ed completed April 29, 2026, 12:58 a.m.
Created at: April 16, 2026, 8:43 p.m.