Triple
T5049056
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tokyo Yakult Swallows |
E113739
|
entity |
| Predicate | sponsor |
P67
|
FINISHED |
| Object | Yakult Honsha |
E488269
|
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: Yakult Honsha | Statement: [Tokyo Yakult Swallows, sponsor, Yakult Honsha]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Yakult Honsha Context triple: [Tokyo Yakult Swallows, sponsor, Yakult Honsha]
-
A.
Yakult Honsha
chosen
Yakult Honsha is a Japanese company best known for producing Yakult probiotic drinks and other dairy-based beverages.
-
B.
Ezaki Glico Co., Ltd.
Ezaki Glico Co., Ltd. is a Japanese confectionery and food company best known for products like Pocky and Pretz, as well as its iconic advertising presence in Osaka.
-
C.
Nissin Foods
Nissin Foods is a Japanese food company best known for inventing instant ramen and the Cup Noodles brand.
-
D.
Kyo-ya Company
Kyo-ya Company is a hospitality and real estate firm best known for owning and operating prominent resort properties in Hawaii, including the historic Royal Hawaiian Hotel in Waikiki.
-
E.
Yoshimoto Kogyo
Yoshimoto Kogyo is a major Japanese entertainment conglomerate best known for managing comedians and producing comedy shows, theater, television, and other media.
- 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_69bd44391fc48190a311ce9c826c209b |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd74249a8c8190952680aee06a9286 |
completed | March 20, 2026, 4:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bea47e5ba0819088217a9ad3ce2b0a |
completed | March 21, 2026, 2 p.m. |
Created at: March 20, 2026, 1:37 p.m.