Triple
T12564130
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Havas |
E295423
|
entity |
| Predicate | hasSubsidiary |
P254
|
FINISHED |
| Object | Havas Creative |
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: Havas Creative | Statement: [Havas, hasSubsidiary, Havas Creative]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Havas Creative Context triple: [Havas, hasSubsidiary, Havas Creative]
-
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.
Wunderman
Wunderman is a global marketing and advertising agency known for its data-driven, digital-first campaigns and customer relationship management services.
-
C.
Wolff Olins
Wolff Olins is a global brand consultancy known for creating bold and sometimes controversial visual identities for major organizations and events.
-
D.
Saatchi & Saatchi
Saatchi & Saatchi is a global advertising agency network renowned for its creative campaigns and influential role in the modern advertising industry.
-
E.
Ogilvy & Mather
Ogilvy & Mather is a major global advertising agency known for its influential marketing campaigns and brand-building work for leading companies worldwide.
- 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_69d6ad9cac2c81908e8a7bed82d1e21d |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d95494ae1c81908b9ee14b8ef92a65 |
completed | April 10, 2026, 7:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6558da7e0819086860bfaf394e2d8 |
completed | May 2, 2026, 7:50 p.m. |
Created at: April 8, 2026, 11:49 p.m.