Triple
T14933189
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yūsaku Kamekura |
E372320
|
entity |
| Predicate | employer |
P7
|
FINISHED |
| Object | Nippon Kōbō |
E360249
|
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 Kōbō | Statement: [Yūsaku Kamekura, employer, Nippon Kōbō]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nippon Kōbō Context triple: [Yūsaku Kamekura, employer, Nippon Kōbō]
-
A.
Nippon Kobo
chosen
Nippon Kobo was a Japanese design and architecture firm active in the mid-20th century, known for its collaborations with prominent modernist designers such as Charlotte Perriand.
-
B.
Yoshimoto Kogyo
Yoshimoto Kogyo is a major Japanese entertainment conglomerate best known for managing comedians and producing comedy shows, theater, television, and other media.
-
C.
Komatsu Limited
Komatsu Limited is a major Japanese multinational corporation that manufactures construction, mining, and military equipment.
-
D.
Keio Corporation
Keio Corporation is a major Japanese private railway and transportation company operating rail lines and related services in the Tokyo metropolitan area.
-
E.
Obayashi Corporation
Obayashi Corporation is a major Japanese construction and engineering company known for its involvement in large-scale infrastructure and building projects worldwide.
- 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_69d85cc9da0c81908d583ca3f63a3908 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded646a0808190ba5c0c91bde011c5 |
completed | April 15, 2026, 12:05 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe968bbbac8190a258c42b226f9def |
completed | May 9, 2026, 2:06 a.m. |
Created at: April 10, 2026, 2:37 a.m.