Triple
T22421568
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nikon Corporation |
E554260
|
entity |
| Predicate | formerName |
P65
|
FINISHED |
| Object | Nippon Kogaku K.K. |
E554260
|
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: Nippon Kogaku K.K. | Statement: [Nikon Corporation, formerName, Nippon Kogaku K.K.]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nippon Kogaku K.K. Context triple: [Nikon Corporation, formerName, Nippon Kogaku K.K.]
-
A.
Nikon Corporation
chosen
Nikon Corporation is a Japanese multinational company renowned for its cameras, imaging products, and precision optical equipment.
-
B.
Olympus Corporation
Olympus Corporation is a Japanese multinational company best known for its optical and imaging products, including cameras, medical endoscopes, and scientific equipment.
-
C.
Nikon
Nikon was a 17th-century Patriarch of Moscow and All Russia known for initiating major liturgical reforms that led to the Raskol (schism) in the Russian Orthodox Church.
-
D.
Nikon
Nikon is a figure associated with the Telchines, a group of mythical craftsmen and sorcerers from ancient Greek mythology.
-
E.
Kowa Company, Ltd.
Kowa Company, Ltd. is a Japanese multinational corporation involved in pharmaceuticals, textiles, and various consumer products.
- 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_69e11e4f2d0c819091aa3558ea2ee630 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f1594b08d88190bb61a30397d0ffa5 |
completed | April 29, 2026, 1:05 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0af0ee77208190b037b3baea224767 |
completed | May 18, 2026, 10:58 a.m. |
Created at: April 16, 2026, 8:46 p.m.