Triple
T3282182
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ogilvy & Mather |
E68896
|
entity |
| Predicate | notableClient |
P7186
|
FINISHED |
| Object | Dove |
E297549
|
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: Dove | Statement: [Ogilvy & Mather, notableClient, Dove]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dove Context triple: [Ogilvy & Mather, notableClient, Dove]
-
A.
Dove
chosen
Dove is a global personal care brand known for its moisturizing soaps, body washes, and beauty products, as well as its marketing campaigns promoting real beauty and body positivity.
-
B.
The Dove
The Dove is a name commonly associated with peace, purity, and gentleness, often used for churches, ships, or symbolic figures.
-
C.
Crest
Crest is a well-known oral care brand, particularly recognized for its toothpastes and whitening products.
-
D.
Crest
Crest is a historic town in southeastern France’s Drôme department, best known for its medieval tower, one of the tallest castle keeps in Europe.
-
E.
Lifebuoy
Lifebuoy is a long-established global soap and hygiene brand known for its antibacterial products and health-focused marketing.
- 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_69ad859c463481909ca4be267336c290 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb0345d448190a1f936abe7748e33 |
completed | March 8, 2026, 5:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b2e85528c88190b1e98c680baf3fa8 |
completed | March 12, 2026, 4:22 p.m. |
Created at: March 8, 2026, 3:10 p.m.