Triple
T186204
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shibuya, Tokyo, Japan |
E3985
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Harajuku
Harajuku is a vibrant Tokyo district famous for its youth culture, eclectic street fashion, and trendy shopping and entertainment spots.
|
E53370
|
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: Harajuku | Statement: [Shibuya, Tokyo, Japan, contains, Harajuku]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Harajuku Context triple: [Shibuya, Tokyo, Japan, contains, Harajuku]
-
A.
Moriguchi
Moriguchi is a city in Japan’s Kansai region that forms part of the Osaka metropolitan area and serves as a residential and commercial hub.
-
B.
Toyonaka
Toyonaka is a suburban city in Japan’s Kansai region known for its residential neighborhoods, educational institutions, and proximity to central Osaka.
-
C.
Shinsaibashi
Shinsaibashi is a major shopping and entertainment district in central Osaka, Japan, known for its covered arcade, fashion boutiques, and vibrant nightlife.
-
D.
Yokohama
Yokohama is Japan’s second-largest city and a major international port located just south of Tokyo.
-
E.
Daikanyama
Daikanyama is a trendy, upscale neighborhood in Tokyo known for its stylish boutiques, cafes, and relaxed, residential atmosphere.
- 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: Harajuku Triple: [Shibuya, Tokyo, Japan, contains, Harajuku]
Generated description
Harajuku is a vibrant Tokyo district famous for its youth culture, eclectic street fashion, and trendy shopping and entertainment spots.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Harajuku Target entity description: Harajuku is a vibrant Tokyo district famous for its youth culture, eclectic street fashion, and trendy shopping and entertainment spots.
-
A.
Moriguchi
Moriguchi is a city in Japan’s Kansai region that forms part of the Osaka metropolitan area and serves as a residential and commercial hub.
-
B.
Toyonaka
Toyonaka is a suburban city in Japan’s Kansai region known for its residential neighborhoods, educational institutions, and proximity to central Osaka.
-
C.
Shinsaibashi
Shinsaibashi is a major shopping and entertainment district in central Osaka, Japan, known for its covered arcade, fashion boutiques, and vibrant nightlife.
-
D.
Yokohama
Yokohama is Japan’s second-largest city and a major international port located just south of Tokyo.
-
E.
Daikanyama
Daikanyama is a trendy, upscale neighborhood in Tokyo known for its stylish boutiques, cafes, and relaxed, residential atmosphere.
- 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_69a25497e2f08190a040f8c6e1842643 |
completed | Feb. 28, 2026, 2:36 a.m. |
| NER | Named-entity recognition | batch_69a2594809288190b3d3b1283e7e0d00 |
completed | Feb. 28, 2026, 2:56 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a4253cbdb88190a4db08c9a91bc15a |
completed | March 1, 2026, 11:38 a.m. |
| NEDg | Description generation | batch_69a4256f2c488190a0373af74b0144c0 |
completed | March 1, 2026, 11:39 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69a4290798f88190ae52f0fe6c456498 |
completed | March 1, 2026, 11:54 a.m. |
Created at: Feb. 28, 2026, 2:40 a.m.