Triple
T5936596
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 吉田茂 |
E132059
|
entity |
| Predicate | 死亡地 |
P21
|
FINISHED |
| Object |
日本・東京都港区
日本・東京都港区は、東京湾に面し多くの大企業本社や大使館、商業施設が集まる東京都心の主要な行政区の一つです。
|
E557098
|
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: 日本・東京都港区 | Statement: [吉田茂, 死亡地, 日本・東京都港区]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: 日本・東京都港区 Context triple: [吉田茂, 死亡地, 日本・東京都港区]
-
A.
Itabashi, Tokyo
Itabashi, Tokyo is one of Tokyo's 23 special wards, located in the northwestern part of the metropolis and known as a primarily residential and commercial area.
-
B.
Toshima, Tokyo
Toshima, Tokyo is a special ward in northwestern Tokyo known for its major commercial and entertainment hub Ikebukuro and its mix of residential, educational, and cultural institutions.
-
C.
Kōtō, Tokyo, Japan
Kōtō is a special ward in eastern Tokyo known for its waterfront areas, reclaimed land, and a mix of residential neighborhoods, commercial districts, and large-scale facilities.
-
D.
Ichigaya district, Tokyo
Ichigaya district, Tokyo is a central Tokyo neighborhood known for hosting major government and defense institutions, including Japan’s Ministry of Defense.
-
E.
Bunkyo, Tokyo
Bunkyo, Tokyo is a central special ward of Tokyo known for its educational institutions, cultural sites, and major sports venues such as the Tokyo Dome.
- 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: 日本・東京都港区 Triple: [吉田茂, 死亡地, 日本・東京都港区]
Generated description
日本・東京都港区は、東京湾に面し多くの大企業本社や大使館、商業施設が集まる東京都心の主要な行政区の一つです。
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: 日本・東京都港区 Target entity description: 日本・東京都港区は、東京湾に面し多くの大企業本社や大使館、商業施設が集まる東京都心の主要な行政区の一つです。
-
A.
Itabashi, Tokyo
Itabashi, Tokyo is one of Tokyo's 23 special wards, located in the northwestern part of the metropolis and known as a primarily residential and commercial area.
-
B.
Toshima, Tokyo
Toshima, Tokyo is a special ward in northwestern Tokyo known for its major commercial and entertainment hub Ikebukuro and its mix of residential, educational, and cultural institutions.
-
C.
Kōtō, Tokyo, Japan
Kōtō is a special ward in eastern Tokyo known for its waterfront areas, reclaimed land, and a mix of residential neighborhoods, commercial districts, and large-scale facilities.
-
D.
Ichigaya district, Tokyo
Ichigaya district, Tokyo is a central Tokyo neighborhood known for hosting major government and defense institutions, including Japan’s Ministry of Defense.
-
E.
Bunkyo, Tokyo
Bunkyo, Tokyo is a central special ward of Tokyo known for its educational institutions, cultural sites, and major sports venues such as the Tokyo Dome.
- 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_69c0085c55dc8190aa90e242c956e2fa |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c038eca9688190adeed21df058daf1 |
completed | March 22, 2026, 6:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c0c06f979881908d7e98ee674f1ff2 |
completed | March 23, 2026, 4:24 a.m. |
| NEDg | Description generation | batch_69c0c329b1108190ac4fe897e2be9946 |
completed | March 23, 2026, 4:35 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c0c3a81a608190a39283b4df0ab4b9 |
completed | March 23, 2026, 4:38 a.m. |
Created at: March 22, 2026, 4:01 p.m.