Triple
T20063525
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kobe, Hyogo, Japan |
E499546
|
entity |
| Predicate | knownFor |
P22
|
FINISHED |
| Object | Kobe beef |
—
|
NE NERFINISHED |
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: Kobe beef | Statement: [Kobe, Hyogo, Japan, knownFor, Kobe beef]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kobe beef Context triple: [Kobe, Hyogo, Japan, knownFor, Kobe beef]
-
A.
Kobe beef
chosen
Kobe beef is a highly prized, richly marbled wagyu beef from Japan renowned for its exceptional tenderness and flavor.
-
B.
Wagyu beef
Wagyu beef is a highly prized Japanese beef known for its exceptional marbling, tenderness, and rich, buttery flavor.
-
C.
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.
-
D.
Matsusaka beef
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.
-
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 (2 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_69da6276bcf48190aabbf279192a5fb4 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e66377b6b48190a0a37279f285123e |
completed | April 20, 2026, 5:33 p.m. |
Created at: April 11, 2026, 3:39 p.m.