Triple
T11278756
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tokyo Midtown |
E267005
|
entity |
| Predicate | district |
P2709
|
FINISHED |
| Object | Roppongi district |
E72625
|
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: Roppongi district | Statement: [Tokyo Midtown, district, Roppongi district]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Roppongi district Context triple: [Tokyo Midtown, district, Roppongi district]
-
A.
Roppongi
chosen
Roppongi is a central Tokyo district famous for its vibrant nightlife, international community, and major art and entertainment complexes.
-
B.
Akasaka
Akasaka is a central Tokyo district known for its business centers, upscale hotels, and vibrant nightlife.
-
C.
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.
-
D.
Shibuya
Shibuya is a major commercial and entertainment district in Tokyo, Japan, famous for its bustling streets, youth culture, and iconic landmarks.
-
E.
Omotesando district
Omotesando district is a fashionable Tokyo neighborhood known for its tree-lined avenue, high-end boutiques, modern architecture, and trendy cafes.
- 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_69d6aac8c2f48190ad0596f1f89f0470 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e967ebb4819080b09ed3cec44e77 |
completed | April 9, 2026, 6:01 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f684c471b88190a4c79d907152b492 |
completed | May 2, 2026, 11:12 p.m. |
Created at: April 8, 2026, 9:31 p.m.