Triple

T14704297
Position Surface form Disambiguated ID Type / Status
Subject Émile Meyerson E345384 entity
Predicate employer P7 FINISHED
Object Agence Havas E295423 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: Agence Havas | Statement: [Émile Meyerson, employer, Agence Havas]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Agence Havas
Context triple: [Émile Meyerson, employer, Agence Havas]
  • A. Havas chosen
    Havas is a major global advertising and communications group headquartered in France, known for its extensive network of creative, media, and marketing agencies.
  • B. 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.
  • C. 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.
  • D. Walter Thompson
    Walter Thompson is an editor known for his work on the film "Pitfall."
  • E. Publicis Groupe
    Publicis Groupe is a major French multinational advertising and communications company and one of the world’s largest marketing services groups.
  • 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_69d822e4a8c08190a155df736bb7bc13 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb6071e5c8190bb5509c859135c2d completed April 14, 2026, 9:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69fdf087ce8c819081a7186df67bcf1f completed May 8, 2026, 2:17 p.m.
Created at: April 10, 2026, 1:28 a.m.