Triple
T3014245
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Naniwa-ku |
E82297
|
entity |
| Predicate | knownFor |
P22
|
FINISHED |
| Object |
Den Den Town
Den Den Town is Osaka’s main electronics and otaku shopping district, known for its anime, manga, game shops, and discount electronics stores.
|
E318688
|
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: Den Den Town | Statement: [Naniwa-ku, knownFor, Den Den Town]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Den Den Town Context triple: [Naniwa-ku, knownFor, Den Den Town]
-
A.
Kiddyland
Kiddyland is a children’s amusement area within Playland Park featuring kid-friendly rides and attractions.
-
B.
Tokyo Chiken
Tokyo Chiken is the commonly used abbreviated name for the Tokyo District Public Prosecutors Office, a key prosecutorial authority in Japan’s capital.
-
C.
Plon-Plon
Plon-Plon was the popular nickname of Prince Napoléon-Jérôme Bonaparte, a 19th-century French imperial prince and cousin of Emperor Napoleon III.
-
D.
Honancho
Honancho is a neighborhood in Tokyo, Japan, known as a residential area with convenient access to central city districts via the Tokyo Metro Marunouchi Line.
-
E.
Bde Maka Ska
Bde Maka Ska is the largest lake in Minneapolis, Minnesota, popular for recreation and known as part of the city’s Chain of Lakes.
- 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: Den Den Town Triple: [Naniwa-ku, knownFor, Den Den Town]
Generated description
Den Den Town is Osaka’s main electronics and otaku shopping district, known for its anime, manga, game shops, and discount electronics stores.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Den Den Town Target entity description: Den Den Town is Osaka’s main electronics and otaku shopping district, known for its anime, manga, game shops, and discount electronics stores.
-
A.
Kiddyland
Kiddyland is a children’s amusement area within Playland Park featuring kid-friendly rides and attractions.
-
B.
Tokyo Chiken
Tokyo Chiken is the commonly used abbreviated name for the Tokyo District Public Prosecutors Office, a key prosecutorial authority in Japan’s capital.
-
C.
Plon-Plon
Plon-Plon was the popular nickname of Prince Napoléon-Jérôme Bonaparte, a 19th-century French imperial prince and cousin of Emperor Napoleon III.
-
D.
Honancho
Honancho is a neighborhood in Tokyo, Japan, known as a residential area with convenient access to central city districts via the Tokyo Metro Marunouchi Line.
-
E.
Bde Maka Ska
Bde Maka Ska is the largest lake in Minneapolis, Minnesota, popular for recreation and known as part of the city’s Chain of Lakes.
- 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_69ad8b1eb53481908c39bbcd1ec104b2 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad9a69e8148190a97507740c9d26a8 |
completed | March 8, 2026, 3:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b12e67e2f88190aa7046e93f3e4126 |
completed | March 11, 2026, 8:57 a.m. |
| NEDg | Description generation | batch_69b12f07ec088190a63e30f8a1f7937a |
completed | March 11, 2026, 8:59 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b1cb6571388190970bae846bfc57a2 |
completed | March 11, 2026, 8:07 p.m. |
Created at: March 8, 2026, 3 p.m.