Triple
T11934275
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 文京区 |
E283998
|
entity |
| Predicate | containsDistrict |
P22582
|
FINISHED |
| Object |
千駄木
千駄木は、東京都文京区に位置する、下町情緒と寺社・古い街並みが残る住宅街エリアです。
|
E954802
|
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: 千駄木 | Statement: [文京区, containsDistrict, 千駄木]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: 千駄木 Context triple: [文京区, containsDistrict, 千駄木]
-
A.
Totsukawa
Totsukawa is a remote mountainous village in Nara Prefecture, Japan, known for its hot springs, suspension bridges, and scenic river valleys.
-
B.
Shirokane
Shirokane is an upscale residential district in Minato, Tokyo, known for its quiet, leafy streets, luxury apartments, and proximity to central business and shopping areas.
-
C.
Marunouchi
Marunouchi is a central Tokyo business district known for its concentration of corporate headquarters, upscale offices, and proximity to Tokyo Station and the Imperial Palace.
-
D.
Yamakoshi
Yamakoshi is a recurring character from the Disney XD sitcom "Pair of Kings," known as a mystical fish with prophetic abilities and a quirky, comedic presence.
-
E.
Shibukawa
Shibukawa is a city in Gunma Prefecture, Japan, known as a regional transport hub and gateway to nearby hot spring resorts such as Ikaho Onsen.
- 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: 千駄木 Triple: [文京区, containsDistrict, 千駄木]
Generated description
千駄木は、東京都文京区に位置する、下町情緒と寺社・古い街並みが残る住宅街エリアです。
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: 千駄木 Target entity description: 千駄木は、東京都文京区に位置する、下町情緒と寺社・古い街並みが残る住宅街エリアです。
-
A.
Totsukawa
Totsukawa is a remote mountainous village in Nara Prefecture, Japan, known for its hot springs, suspension bridges, and scenic river valleys.
-
B.
Shirokane
Shirokane is an upscale residential district in Minato, Tokyo, known for its quiet, leafy streets, luxury apartments, and proximity to central business and shopping areas.
-
C.
Marunouchi
Marunouchi is a central Tokyo business district known for its concentration of corporate headquarters, upscale offices, and proximity to Tokyo Station and the Imperial Palace.
-
D.
Yamakoshi
Yamakoshi is a recurring character from the Disney XD sitcom "Pair of Kings," known as a mystical fish with prophetic abilities and a quirky, comedic presence.
-
E.
Shibukawa
Shibukawa is a city in Gunma Prefecture, Japan, known as a regional transport hub and gateway to nearby hot spring resorts such as Ikaho Onsen.
- 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.