Triple
T11934270
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 文京区 |
E283998
|
entity |
| Predicate | containsDistrict |
P22582
|
FINISHED |
| Object |
本郷
本郷は、東京都文京区に位置し、東京大学本郷キャンパスなどの教育・文化施設が集まる歴史ある文教地区である。
|
E954798
|
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: 本郷 | Statement: [文京区, containsDistrict, 本郷]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: 本郷 Context triple: [文京区, containsDistrict, 本郷]
-
A.
Nagareyama
Nagareyama is a city in Chiba Prefecture, Japan, known as a residential suburb of the Tokyo metropolitan area with growing commuter access and family-oriented neighborhoods.
-
B.
Mukaishima
Mukaishima is an island in Japan’s Seto Inland Sea that serves as one of the key waypoints along the scenic Shimanami Kaido cycling and driving route.
-
C.
Mikasuki
Mikasuki is a Native American language of the Muskogean family, traditionally spoken by the Miccosukee and some Seminole people in the southeastern United States.
-
D.
Minakami
Minakami is a mountainous town in Gunma Prefecture, Japan, known for its hot springs, outdoor sports, and scenic natural landscapes.
-
E.
Kasukabe
Kasukabe is a city in Japan known for its suburban character within the Greater Tokyo area and as the setting of the popular manga and anime series "Crayon Shin-chan."
- 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: 本郷 Triple: [文京区, containsDistrict, 本郷]
Generated description
本郷は、東京都文京区に位置し、東京大学本郷キャンパスなどの教育・文化施設が集まる歴史ある文教地区である。
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: 本郷 Target entity description: 本郷は、東京都文京区に位置し、東京大学本郷キャンパスなどの教育・文化施設が集まる歴史ある文教地区である。
-
A.
Nagareyama
Nagareyama is a city in Chiba Prefecture, Japan, known as a residential suburb of the Tokyo metropolitan area with growing commuter access and family-oriented neighborhoods.
-
B.
Mukaishima
Mukaishima is an island in Japan’s Seto Inland Sea that serves as one of the key waypoints along the scenic Shimanami Kaido cycling and driving route.
-
C.
Mikasuki
Mikasuki is a Native American language of the Muskogean family, traditionally spoken by the Miccosukee and some Seminole people in the southeastern United States.
-
D.
Minakami
Minakami is a mountainous town in Gunma Prefecture, Japan, known for its hot springs, outdoor sports, and scenic natural landscapes.
-
E.
Kasukabe
Kasukabe is a city in Japan known for its suburban character within the Greater Tokyo area and as the setting of the popular manga and anime series "Crayon Shin-chan."
- 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_69d6ab2ce9c48190b5d39511b524f666 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d90306fcf48190a963d2d1932288d1 |
completed | April 10, 2026, 2:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f4407cc2388190b0f849fbeed89ab7 |
completed | May 1, 2026, 5:56 a.m. |
| NEDg | Description generation | batch_69f448fc874081908fe05f9d8aff11a3 |
completed | May 1, 2026, 6:32 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f44afdc7b08190bdf47cfcb94c34c8 |
completed | May 1, 2026, 6:41 a.m. |
Created at: April 8, 2026, 9:45 p.m.