Triple
T14116580
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Crest |
E339790
|
entity |
| Predicate | hasProductLine |
P3585
|
FINISHED |
| Object | Crest Pro-Health |
E339790
|
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: Crest Pro-Health | Statement: [Crest, hasProductLine, Crest Pro-Health]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Crest Pro-Health Context triple: [Crest, hasProductLine, Crest Pro-Health]
-
A.
Aquafresh
Aquafresh is a popular brand of toothpaste known for its distinctive striped appearance and range of oral care products.
-
B.
Pepsodent
Pepsodent is a long-established toothpaste brand known for its focus on cavity protection and oral hygiene, marketed globally by major consumer goods companies.
-
C.
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.
-
D.
Crest
chosen
Crest is a well-known oral care brand, particularly recognized for its toothpastes and whitening products.
-
E.
Colgate
Colgate is a small village in West Sussex, England, known for its rural character and proximity to Horsham.
- 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_69d81c6a95b481909e39111e0c1f31ee |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de6010a03c81909f5f160f8d1fa8fa |
completed | April 14, 2026, 3:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fcdf0641008190b88efacc02ba5314 |
completed | May 7, 2026, 6:50 p.m. |
Created at: April 9, 2026, 10:22 p.m.