Triple
T14116297
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Procter & Gamble Company |
E339784
|
entity |
| Predicate | brand |
P1500
|
FINISHED |
| Object | Crest |
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 | Statement: [Procter & Gamble Company, brand, Crest]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Crest Context triple: [Procter & Gamble Company, brand, Crest]
-
A.
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.
-
B.
Crest
chosen
Crest is a well-known oral care brand, particularly recognized for its toothpastes and whitening products.
-
C.
Zarvos
Zarvos is a surname most notably associated with Brazilian pianist and film composer Marcelo Zarvos.
-
D.
Colgate Thirteen
Colgate Thirteen is a renowned all-male a cappella group from Colgate University known for performing at high-profile events, including the national anthem at Super Bowl XIII.
-
E.
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.
- 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_69fcd0baa328819099511dfa7b9666d3 |
completed | May 7, 2026, 5:49 p.m. |
Created at: April 9, 2026, 10:22 p.m.