Triple
T16169621
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | McCann Erickson |
E392398
|
entity |
| Predicate | hasClient |
P734
|
FINISHED |
| Object | Nestlé |
E27582
|
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: Nestlé | Statement: [McCann Erickson, hasClient, Nestlé]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nestlé Context triple: [McCann Erickson, hasClient, Nestlé]
-
A.
Nestlé
chosen
Nestlé is a Swiss multinational food and beverage conglomerate and one of the world’s largest consumer goods companies.
-
B.
Danone
Danone is a multinational French food-products corporation best known for its dairy, plant-based, and bottled water brands.
-
C.
Mondelez International
Mondelez International is a global snack and confectionery company known for brands like Oreo, Cadbury, and Toblerone.
-
D.
Kraft Foods
Kraft Foods is a major American food and beverage company known for producing a wide range of packaged grocery products and iconic brands such as Kraft cheese and Oscar Mayer.
-
E.
Post Holdings
Post Holdings is a U.S.-based consumer packaged goods holding company best known for owning and operating major breakfast cereal and food brands.
- 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_69d87f1d32208190942e4e499a80c18c |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e21eb5e6d881908749683091afa90c |
completed | April 17, 2026, 11:51 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fff7bb6aac8190a33607abfe9a32d0 |
completed | May 10, 2026, 3:12 a.m. |
Created at: April 10, 2026, 5:02 a.m.