Triple
T8611483
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SD Association |
E203922
|
entity |
| Predicate | hasMember |
P10
|
FINISHED |
| Object | Nikon |
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: Nikon | Statement: [SD Association, hasMember, Nikon]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nikon Context triple: [SD Association, hasMember, Nikon]
-
A.
Nikon Corporation
chosen
Nikon Corporation is a Japanese multinational company renowned for its cameras, imaging products, and precision optical equipment.
-
B.
Nikon Z series
The Nikon Z series is Nikon’s line of full-frame and APS-C mirrorless interchangeable-lens cameras designed to rival systems like Sony’s Alpha lineup.
-
C.
Kodak
Kodak is an unincorporated community in Sevier County, Tennessee, known as a growing residential and commercial area near the Great Smoky Mountains and the city of Knoxville.
-
D.
Yodobashi Camera Co., Ltd.
Yodobashi Camera Co., Ltd. is a major Japanese consumer electronics retail chain known for its large multi-story stores offering a wide range of electronics, appliances, and related goods.
-
E.
Panasonic
Panasonic is a major Japanese multinational electronics company known for its wide range of consumer electronics, home appliances, and industrial solutions.
- 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_69ca832c23e4819095a9f3eea4a21828 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cc46fc31e08190aab5ab8f92f3315c |
completed | March 31, 2026, 10:13 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cea91456a88190a7416b0f1a0327d6 |
completed | April 2, 2026, 5:36 p.m. |
Created at: March 30, 2026, 6:25 p.m.