Triple
T9191317
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 黒川紀章 |
E220593
|
entity |
| Predicate | 代表作 |
P4
|
FINISHED |
| Object |
ナゴヤシティタワー55
ナゴヤシティタワー55は、建築家・黒川紀章が手がけた名古屋市にある高層複合ビルで、その近未来的なデザインで知られる建築作品である。
|
E783953
|
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: ナゴヤシティタワー55 | Statement: [黒川紀章, 代表作, ナゴヤシティタワー55]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: ナゴヤシティタワー55 Context triple: [黒川紀章, 代表作, ナゴヤシティタワー55]
-
A.
Yokohama Landmark Tower
Yokohama Landmark Tower is a prominent skyscraper in Yokohama, Japan, known for its height, office and hotel facilities, and observation deck offering panoramic city and bay views.
-
B.
Nagoya TV Tower
Nagoya TV Tower is a historic steel observation and broadcasting tower in central Nagoya, Japan, known as a prominent city landmark and tourist attraction.
-
C.
Shinjuku Park Tower
Shinjuku Park Tower is a prominent high-rise complex in Tokyo known for its distinctive tiered design and housing the Park Hyatt Tokyo hotel.
-
D.
Shinjuku L Tower
Shinjuku L Tower is a high-rise office building located in the Shinjuku district of Tokyo, Japan.
-
E.
Abeno Harukas
Abeno Harukas is a 300-meter-tall skyscraper in Osaka, Japan, known as one of the country's tallest buildings and a major commercial, cultural, and observation 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: ナゴヤシティタワー55 Triple: [黒川紀章, 代表作, ナゴヤシティタワー55]
Generated description
ナゴヤシティタワー55は、建築家・黒川紀章が手がけた名古屋市にある高層複合ビルで、その近未来的なデザインで知られる建築作品である。
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: ナゴヤシティタワー55 Target entity description: ナゴヤシティタワー55は、建築家・黒川紀章が手がけた名古屋市にある高層複合ビルで、その近未来的なデザインで知られる建築作品である。
-
A.
Yokohama Landmark Tower
Yokohama Landmark Tower is a prominent skyscraper in Yokohama, Japan, known for its height, office and hotel facilities, and observation deck offering panoramic city and bay views.
-
B.
Nagoya TV Tower
Nagoya TV Tower is a historic steel observation and broadcasting tower in central Nagoya, Japan, known as a prominent city landmark and tourist attraction.
-
C.
Shinjuku Park Tower
Shinjuku Park Tower is a prominent high-rise complex in Tokyo known for its distinctive tiered design and housing the Park Hyatt Tokyo hotel.
-
D.
Shinjuku L Tower
Shinjuku L Tower is a high-rise office building located in the Shinjuku district of Tokyo, Japan.
-
E.
Abeno Harukas
Abeno Harukas is a 300-meter-tall skyscraper in Osaka, Japan, known as one of the country's tallest buildings and a major commercial, cultural, and observation 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_69ca83e7ba70819088b74866d9da2c30 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69ccd5bf25c081909e651b67ef8ecc33 |
completed | April 1, 2026, 8:22 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d05c272f508190aade1769c88cf16d |
completed | April 4, 2026, 12:32 a.m. |
| NEDg | Description generation | batch_69d05cda59f88190bcde5a91aec2f9dd |
completed | April 4, 2026, 12:35 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d05ddd28008190b82c42220871e73f |
completed | April 4, 2026, 12:39 a.m. |
Created at: March 30, 2026, 7:24 p.m.