Triple
T7773699
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shoto |
E179135
|
entity |
| Predicate | near |
P350
|
FINISHED |
| Object |
Tomigaya
Tomigaya is a trendy residential neighborhood in Tokyo’s Shibuya ward, known for its quiet streets, stylish cafés, and proximity to Yoyogi Park.
|
E689490
|
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: Tomigaya | Statement: [Shoto, near, Tomigaya]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tomigaya Context triple: [Shoto, near, Tomigaya]
-
A.
Toshima
Toshima is a special ward in northwest Tokyo known for the major commercial and entertainment hub of Ikebukuro and its dense urban residential districts.
-
B.
Moriyama
Moriyama is a Japanese city located in Shiga Prefecture, known for its position near Lake Biwa and its blend of residential areas and historical sites.
-
C.
Takatsuki
Takatsuki is a city in northern Osaka Prefecture, Japan, known as a residential and commercial hub between Osaka and Kyoto.
-
D.
Musashi-Koyama
Musashi-Koyama is a lively neighborhood in Tokyo known for its long covered shopping street, local eateries, and convenient urban living.
-
E.
Ichigaya
Ichigaya is a central Tokyo district known for its major railway station, government and educational institutions, and proximity to the Imperial Palace area.
- 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: Tomigaya Triple: [Shoto, near, Tomigaya]
Generated description
Tomigaya is a trendy residential neighborhood in Tokyo’s Shibuya ward, known for its quiet streets, stylish cafés, and proximity to Yoyogi Park.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Tomigaya Target entity description: Tomigaya is a trendy residential neighborhood in Tokyo’s Shibuya ward, known for its quiet streets, stylish cafés, and proximity to Yoyogi Park.
-
A.
Toshima
Toshima is a special ward in northwest Tokyo known for the major commercial and entertainment hub of Ikebukuro and its dense urban residential districts.
-
B.
Moriyama
Moriyama is a Japanese city located in Shiga Prefecture, known for its position near Lake Biwa and its blend of residential areas and historical sites.
-
C.
Takatsuki
Takatsuki is a city in northern Osaka Prefecture, Japan, known as a residential and commercial hub between Osaka and Kyoto.
-
D.
Musashi-Koyama
Musashi-Koyama is a lively neighborhood in Tokyo known for its long covered shopping street, local eateries, and convenient urban living.
-
E.
Ichigaya
Ichigaya is a central Tokyo district known for its major railway station, government and educational institutions, and proximity to the Imperial Palace area.
- 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_69c69f30602c819082ab52cd4af5c592 |
completed | March 27, 2026, 3:16 p.m. |
| NER | Named-entity recognition | batch_69c70461b3e48190bf1e4d4f9e6bb08e |
completed | March 27, 2026, 10:27 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c9009dfc288190b7e1e77a5d28e64f |
completed | March 29, 2026, 10:36 a.m. |
| NEDg | Description generation | batch_69c90133654081908fcf2c01027fed0f |
completed | March 29, 2026, 10:38 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c90182232c81909fd9461bb176fdbf |
completed | March 29, 2026, 10:40 a.m. |
Created at: March 27, 2026, 4:11 p.m.