Triple
T20165239
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ricoh 2A03 |
E491810
|
entity |
| Predicate | manufacturer |
P490
|
FINISHED |
| Object | Ricoh |
—
|
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: Ricoh | Statement: [Ricoh 2A03, manufacturer, Ricoh]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ricoh Context triple: [Ricoh 2A03, manufacturer, Ricoh]
-
A.
Ricoh
chosen
Ricoh is a Japanese multinational imaging and electronics company best known for its cameras, printers, copiers, and office equipment solutions.
-
B.
Konica Minolta
Konica Minolta is a Japanese multinational technology company best known for its imaging products, including printers, copiers, and optical devices.
-
C.
Canon Inc.
Canon Inc. is a Japanese multinational corporation renowned for its imaging and optical products, including cameras, camcorders, printers, and related equipment.
-
D.
Xerox
Xerox is an American corporation best known for pioneering photocopiers and influential computing innovations, including early graphical user interfaces and office software.
-
E.
Ricoh Manresa
Ricoh Manresa is a professional basketball club based in Manresa, Spain, that competes in the Spanish basketball league system.
- 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_69da6266c6888190bc1a3ecf24814d34 |
completed | April 11, 2026, 3:01 p.m. |
| NER | Named-entity recognition | batch_69e668442d2c81908bb1a0fac9895b5e |
completed | April 20, 2026, 5:54 p.m. |
Created at: April 11, 2026, 11:35 p.m.