Triple
T1860600
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Taitō |
E34802
|
entity |
| Predicate | hasHistoricDistrict |
P295
|
FINISHED |
| Object | Asakusa |
E72187
|
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: Asakusa | Statement: [Taitō, hasHistoricDistrict, Asakusa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Asakusa Context triple: [Taitō, hasHistoricDistrict, Asakusa]
-
A.
Asakusa
chosen
Asakusa is a historic district in Tokyo best known for its ancient Sensō-ji Temple, traditional shopping streets, and preserved old-town atmosphere.
-
B.
Ueno
Ueno is a major district in Tokyo known for Ueno Park, its museums, zoo, and busy transportation hub.
-
C.
Fushimi
Fushimi is a historic district in Kyoto, Japan, known for its castle and its association with key events and figures of the late Sengoku period.
-
D.
Bunkyo, Tokyo
Bunkyo, Tokyo is a central special ward of Tokyo known for its educational institutions, cultural sites, and major sports venues such as the Tokyo Dome.
-
E.
Toyonaka
Toyonaka is a suburban city in Japan’s Kansai region known for its residential neighborhoods, educational institutions, and proximity to central Osaka.
- 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_69a88600b2f88190bc09303e68ab517e |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69abb09caee881908efe8aa38471298c |
completed | March 7, 2026, 4:59 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b0fc189de08190b88849333d824c5b |
completed | March 11, 2026, 5:22 a.m. |
Created at: March 4, 2026, 7:34 p.m.