Triple
T577197
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Casio |
E13780
|
entity |
| Predicate | brand |
P1500
|
FINISHED |
| Object | Casio Privia |
E13780
|
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: Casio Privia | Statement: [Casio, brand, Casio Privia]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Casio Privia Context triple: [Casio, brand, Casio Privia]
-
A.
Casio
chosen
Casio is a Japanese electronics company best known for its durable digital watches, calculators, and consumer electronics.
-
B.
Claviere
Claviere is a small alpine village and ski resort in northwestern Italy, known for its mountain scenery and winter sports facilities.
-
C.
Denon Wing
Denon Wing is one of the main wings of the Louvre Museum in Paris, housing many of its most famous artworks, including Leonardo da Vinci’s Mona Lisa.
-
D.
Piano
Piano is a large, versatile keyboard musical instrument that produces sound by hammers striking strings, widely used in classical, jazz, and popular music.
-
E.
88-Keys
88-Keys is an American hip-hop producer and DJ known for his soulful, sample-based beats and collaborations with prominent artists such as Kanye West and John Legend.
- 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_69a4933fa4d88190a7949cc83c08c5c1 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a49b68cc808190b1ba45bdad78443d |
completed | March 1, 2026, 8:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a501bfb6408190bf7e1f462f39723d |
completed | March 2, 2026, 3:19 a.m. |
Created at: March 1, 2026, 7:33 p.m.