Triple
T10268477
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tokyo Dining |
E240772
|
entity |
| Predicate | adjacentTo |
P224
|
FINISHED |
| Object | Teppan Edo |
E240771
|
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: Teppan Edo | Statement: [Tokyo Dining, adjacentTo, Teppan Edo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Teppan Edo Context triple: [Tokyo Dining, adjacentTo, Teppan Edo]
-
A.
Teppan Edo
chosen
Teppan Edo is a teppanyaki-style Japanese restaurant located in the Japan Pavilion at EPCOT in Walt Disney World Resort.
-
B.
Hibachi
Hibachi is the nickname of former NBA All-Star guard Gilbert Arenas, known for his explosive scoring and long-range shooting.
-
C.
Kamado Jigoku
Kamado Jigoku is one of Beppu’s famous “hell” hot spring attractions, known for its vividly colored boiling pools and dramatic geothermal scenery.
-
D.
Oshiage
Oshiage is a district in Sumida, Tokyo, best known as the location of the Tokyo Skytree and its surrounding commercial complex.
-
E.
Ma Kai
Ma Kai is a Chinese politician who served as a Vice Premier of the State Council and played a key role in the country’s economic and financial policymaking.
- 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_69d381a94c1881908fc38fc263d9b9c2 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d27033c081908721f6f8568059f2 |
completed | April 7, 2026, 9:46 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d6f80c25888190a3e8a2c513df7043 |
completed | April 9, 2026, 12:51 a.m. |
Created at: April 6, 2026, 11:34 a.m.