Triple
T21497788
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Young & Rubicam |
E530399
|
entity |
| Predicate | hasClient |
P734
|
FINISHED |
| Object | Colgate-Palmolive |
—
|
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: Colgate-Palmolive | Statement: [Young & Rubicam, hasClient, Colgate-Palmolive]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Colgate-Palmolive Context triple: [Young & Rubicam, hasClient, Colgate-Palmolive]
-
A.
Colgate-Palmolive
chosen
Colgate-Palmolive is a global consumer products company best known for its oral care, personal care, home care, and pet nutrition brands.
-
B.
Colgate
Colgate is a small village in West Sussex, England, known for its rural character and proximity to Horsham.
-
C.
Procter & Gamble
Procter & Gamble is a multinational consumer goods corporation known for a wide range of household, personal care, and hygiene brands sold globally.
-
D.
Henkel
Henkel is a German multinational chemical and consumer goods company best known for its brands in laundry, home care, and adhesives.
-
E.
Unilever
Unilever is a multinational consumer goods company known for its wide range of food, personal care, and household products sold globally.
- 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_69e0c45bd15481909fba5910765cdda2 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69e9ea58faa08190ab9f60b0db3c425b |
completed | April 23, 2026, 9:46 a.m. |
Created at: April 16, 2026, 6:23 p.m.