Triple
T262031
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tokyo |
E5560
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Odaiba
Odaiba is a popular high-tech entertainment and shopping district built on a man-made island in Tokyo Bay.
|
E64227
|
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: Odaiba | Statement: [Tokyo, contains, Odaiba]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Odaiba Context triple: [Tokyo, contains, Odaiba]
-
A.
Harajuku
Harajuku is a vibrant Tokyo district famous for its youth culture, eclectic street fashion, and trendy shopping and entertainment spots.
-
B.
Tempozan Harbor Village
Tempozan Harbor Village is a waterfront shopping and entertainment complex in Osaka, Japan, known for attractions like the Tempozan Ferris Wheel and its proximity to the Osaka Aquarium Kaiyukan.
-
C.
Miyashita Park
Miyashita Park is a redeveloped urban park and shopping complex in Shibuya that combines green space, sports facilities, and commercial areas atop a multi-story building.
-
D.
Shibuya Hikarie
Shibuya Hikarie is a major high-rise commercial complex in Tokyo known for its shopping, dining, cultural facilities, and direct connection to Shibuya Station.
-
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: Odaiba Triple: [Tokyo, contains, Odaiba]
Generated description
Odaiba is a popular high-tech entertainment and shopping district built on a man-made island in Tokyo Bay.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Odaiba Target entity description: Odaiba is a popular high-tech entertainment and shopping district built on a man-made island in Tokyo Bay.
-
A.
Harajuku
Harajuku is a vibrant Tokyo district famous for its youth culture, eclectic street fashion, and trendy shopping and entertainment spots.
-
B.
Tempozan Harbor Village
Tempozan Harbor Village is a waterfront shopping and entertainment complex in Osaka, Japan, known for attractions like the Tempozan Ferris Wheel and its proximity to the Osaka Aquarium Kaiyukan.
-
C.
Miyashita Park
Miyashita Park is a redeveloped urban park and shopping complex in Shibuya that combines green space, sports facilities, and commercial areas atop a multi-story building.
-
D.
Shibuya Hikarie
Shibuya Hikarie is a major high-rise commercial complex in Tokyo known for its shopping, dining, cultural facilities, and direct connection to Shibuya Station.
-
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_69a2580a64ac8190ad76e34bb0715b5e |
completed | Feb. 28, 2026, 2:50 a.m. |
| NER | Named-entity recognition | batch_69a25d7428dc8190ae12b12a21fcc6cb |
completed | Feb. 28, 2026, 3:13 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a4a146fcc8819095b8d793864fbab1 |
completed | March 1, 2026, 8:27 p.m. |
| NEDg | Description generation | batch_69a4a1ef80a081908d6a8663e6069f46 |
completed | March 1, 2026, 8:30 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69a4a3164ee48190b11df515250996f8 |
completed | March 1, 2026, 8:35 p.m. |
Created at: Feb. 28, 2026, 2:55 a.m.