Triple
T7998364
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 東京大学大学院総合文化研究科 |
E186182
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | 目黒区 |
E251913
|
NE FINISHED |
How this triple was built (2 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: 目黒区 | Statement: [東京大学大学院総合文化研究科, locatedIn, 目黒区]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: 目黒区 Context triple: [東京大学大学院総合文化研究科, locatedIn, 目黒区]
-
A.
Meguro Ward
chosen
Meguro Ward is a residential and commercial district in southwest Tokyo known for its urban neighborhoods, cultural sites, and convenient rail access to central Tokyo.
-
B.
Shibuya-ku
Shibuya-ku is a major commercial and entertainment ward in central Tokyo, Japan, known for its bustling shopping districts, nightlife, and the iconic Shibuya Crossing.
-
C.
Suginami Ward
Suginami Ward is one of Tokyo’s 23 special wards, known as a largely residential area with numerous parks, local shopping streets, and a strong community atmosphere.
-
D.
東京都港区
東京都港区は、東京湾に面し大使館や企業本社、高級住宅地が集まる東京都心の行政区の一つです。
-
E.
Miyagino-ku
Miyagino-ku is one of the administrative wards of Sendai, Japan, known for its mix of residential areas, commercial facilities, and transportation hubs.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69ca82aaaf24819084b94d18f699ba53 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb3c9a12788190a5607a538f4e07c1 |
completed | March 31, 2026, 3:16 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cbe114372c819086f06e184d5ebde2 |
completed | March 31, 2026, 2:58 p.m. |
Created at: March 30, 2026, 5:17 p.m.