Triple
T19806712
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sasazuka Station |
E475831
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object |
Shibuya
Shibuya is a major commercial and entertainment district in Tokyo, Japan, famous for its busy scramble crossing, shopping, and youth culture.
|
E208724
|
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: Shibuya | Statement: [Sasazuka Station, locatedIn, Shibuya]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Shibuya Context triple: [Sasazuka Station, locatedIn, Shibuya]
-
A.
Shibuya
Shibuya is a major commercial and entertainment district in Tokyo, Japan, famous for its bustling streets, youth culture, and iconic landmarks.
-
B.
Shinjuku
Shinjuku is a major commercial and entertainment district in western Tokyo, known for its busy railway station, skyscrapers, shopping, nightlife, and the Tokyo Metropolitan Government Building.
-
C.
Akasaka
Akasaka is a central Tokyo district known for its business centers, upscale hotels, and vibrant nightlife.
-
D.
Minami-Aoyama
Minami-Aoyama is an upscale district in Tokyo’s Minato ward known for its fashionable boutiques, stylish cafes, and contemporary art galleries.
-
E.
Harajuku
Harajuku is a vibrant Tokyo district famous for its youth culture, eclectic street fashion, and trendy shopping and entertainment spots.
- 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: Shibuya Triple: [Sasazuka Station, locatedIn, Shibuya]
Generated description
Shibuya is a major commercial and entertainment district in Tokyo, Japan, famous for its busy scramble crossing, shopping, and youth culture.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Shibuya Target entity description: Shibuya is a major commercial and entertainment district in Tokyo, Japan, famous for its busy scramble crossing, shopping, and youth culture.
-
A.
Shibuya
chosen
Shibuya is a major commercial and entertainment district in Tokyo, Japan, famous for its bustling streets, youth culture, and iconic landmarks.
-
B.
Shinjuku
Shinjuku is a major commercial and entertainment district in western Tokyo, known for its busy railway station, skyscrapers, shopping, nightlife, and the Tokyo Metropolitan Government Building.
-
C.
Akasaka
Akasaka is a central Tokyo district known for its business centers, upscale hotels, and vibrant nightlife.
-
D.
Minami-Aoyama
Minami-Aoyama is an upscale district in Tokyo’s Minato ward known for its fashionable boutiques, stylish cafes, and contemporary art galleries.
-
E.
Harajuku
Harajuku is a vibrant Tokyo district famous for its youth culture, eclectic street fashion, and trendy shopping and entertainment spots.
- F. None of above.
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_69d8e51bc4208190a1c57d8c5d1b15e4 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e65428f5c48190be6ae0d6a77675d2 |
completed | April 20, 2026, 4:28 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a07c4dfafa48190ab1a30cfa32b6948 |
completed | May 16, 2026, 1:14 a.m. |
| NEDg | Description generation | batch_6a07c6da5da081909bf52e6e56a92e90 |
completed | May 16, 2026, 1:22 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a07c7611ef48190a7dc0619aa2e073b |
completed | May 16, 2026, 1:24 a.m. |
Created at: April 10, 2026, 1:49 p.m.