Triple
T3364879
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chiyoda |
E70810
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Akihabara district |
E71481
|
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: Akihabara district | Statement: [Chiyoda, contains, Akihabara district]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Akihabara district Context triple: [Chiyoda, contains, Akihabara district]
-
A.
Akihabara
chosen
Akihabara is a famous Tokyo district known as a major center for electronics, anime, manga, and otaku culture.
-
B.
Kyobashi commercial district
The Kyobashi commercial district is a bustling business and shopping area in central Tokyo known for its mix of modern office buildings, retail stores, and dining options between Tokyo and Ginza.
-
C.
Shibuya
Shibuya is a major commercial and entertainment district in Tokyo, Japan, famous for its bustling streets, youth culture, and iconic landmarks.
-
D.
Ikebukuro
Ikebukuro is a major commercial and entertainment district in Tokyo known for its large train station, shopping complexes, and vibrant youth culture.
-
E.
Harajuku
Harajuku is a vibrant Tokyo district famous for its youth culture, eclectic street fashion, and trendy shopping and entertainment spots.
- 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_69ad85a729d48190afd789cd8417f289 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb28643f48190b78b0222f8323344 |
completed | March 8, 2026, 5:31 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b67b99c00481908b846c610bd29993 |
completed | March 15, 2026, 9:27 a.m. |
Created at: March 8, 2026, 3:13 p.m.