Triple
T4302761
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Morioka |
E99878
|
entity |
| Predicate | specialtyFood |
P17971
|
FINISHED |
| Object |
Wanko Soba
Wanko Soba is a style of Japanese soba dining where diners rapidly eat many small bowls of noodles, often as a competitive or celebratory challenge.
|
E429365
|
NE FINISHED |
How this triple was built (4 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: Wanko Soba | Statement: [Morioka, specialtyFood, Wanko Soba]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wanko Soba Context triple: [Morioka, specialtyFood, Wanko Soba]
-
A.
Hakata ramen
Hakata ramen is a rich, pork-bone-based Japanese noodle soup style originating from Fukuoka, famed for its creamy tonkotsu broth and thin, firm noodles.
-
B.
Ramenki
Ramenki is a Moscow Metro station serving the Kalininsko–Solntsevskaya Line in the Ramenki District of western Moscow, Russia.
-
C.
kishimen noodles
Kishimen noodles are a type of flat, broad udon noodle from Japan, especially associated with Nagoya cuisine.
-
D.
Tekone-zushi
Tekone-zushi is a regional Japanese dish of marinated raw fish mixed with vinegared rice, traditionally associated with fishermen’s cuisine in Mie Prefecture.
-
E.
Oshiage
Oshiage is a district in Sumida, Tokyo, best known as the location of the Tokyo Skytree and its surrounding commercial complex.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Wanko Soba Triple: [Morioka, specialtyFood, Wanko Soba]
Generated description
Wanko Soba is a style of Japanese soba dining where diners rapidly eat many small bowls of noodles, often as a competitive or celebratory challenge.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Wanko Soba Target entity description: Wanko Soba is a style of Japanese soba dining where diners rapidly eat many small bowls of noodles, often as a competitive or celebratory challenge.
-
A.
Hakata ramen
Hakata ramen is a rich, pork-bone-based Japanese noodle soup style originating from Fukuoka, famed for its creamy tonkotsu broth and thin, firm noodles.
-
B.
Ramenki
Ramenki is a Moscow Metro station serving the Kalininsko–Solntsevskaya Line in the Ramenki District of western Moscow, Russia.
-
C.
kishimen noodles
Kishimen noodles are a type of flat, broad udon noodle from Japan, especially associated with Nagoya cuisine.
-
D.
Tekone-zushi
Tekone-zushi is a regional Japanese dish of marinated raw fish mixed with vinegared rice, traditionally associated with fishermen’s cuisine in Mie Prefecture.
-
E.
Oshiage
Oshiage is a district in Sumida, Tokyo, best known as the location of the Tokyo Skytree and its surrounding commercial complex.
- F. None of above. chosen
Provenance (5 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_69b345528ebc8190b5abc7e95094792d |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b350b66450819089c9ff6ff9f045e5 |
completed | March 12, 2026, 11:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5c7507f1081909cf737dff00542d9 |
completed | March 14, 2026, 8:38 p.m. |
| NEDg | Description generation | batch_69b5c909b7848190bbe00249e0c9e555 |
completed | March 14, 2026, 8:46 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b5c97117088190972bba5dbc1553f7 |
completed | March 14, 2026, 8:47 p.m. |
Created at: March 12, 2026, 11:08 p.m.