Triple
T9894046
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Matsusaka beef |
E181523
|
entity |
| Predicate | JapaneseName |
P744
|
FINISHED |
| Object | 松阪牛 |
E181523
|
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: 松阪牛 | Statement: [Matsusaka beef, JapaneseName, 松阪牛]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: 松阪牛 Context triple: [Matsusaka beef, JapaneseName, 松阪牛]
-
A.
Tajima beef
Tajima beef is a premium, highly marbled wagyu beef from Hyōgo Prefecture in Japan, renowned as the genetic source of famous brands like Kobe beef.
-
B.
Matsusaka beef
chosen
Matsusaka beef is a highly prized, richly marbled wagyu beef from Japan, renowned as one of the country's most luxurious and tender varieties of beef.
-
C.
Kobe beef
Kobe beef is a highly prized, richly marbled wagyu beef from Japan renowned for its exceptional tenderness and flavor.
-
D.
Yonezawa beef
Yonezawa beef is a highly prized wagyu brand from Yonezawa in Yamagata Prefecture, renowned in Japan for its exceptional marbling, tenderness, and rich flavor.
-
E.
Miyazaki beef
Miyazaki beef is a highly prized Japanese wagyu renowned for its exceptional marbling, tenderness, and rich flavor, often considered among the finest beef in the world.
- 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_69ca8283a6708190801af7a25a7ebb9f |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cdb48271d48190b718c7f6b2fe315b |
completed | April 2, 2026, 12:12 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1eb0d984c81908408f90f156624e5 |
completed | April 5, 2026, 4:54 a.m. |
Created at: March 30, 2026, 8:39 p.m.