Triple
T8761182
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Asakusa Station |
E208201
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Taitō |
E34802
|
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: Taitō | Statement: [Asakusa Station, locatedIn, Taitō]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Taitō Context triple: [Asakusa Station, locatedIn, Taitō]
-
A.
Taitō
chosen
Taitō is a special ward in central Tokyo known for its historic districts, traditional temples, and major cultural attractions such as Ueno Park and Asakusa.
-
B.
Task Force 64
Task Force 64 was a U.S. Navy surface combat task force in the Pacific Theater during World War II, noted for its role in night battles such as those off Guadalcanal.
-
C.
Kunio
Kunio is a Japanese masculine given name borne by various notable figures in politics, academia, and the arts.
-
D.
Tokitarō
Tokitarō was the childhood given name of the renowned Japanese ukiyo-e artist Katsushika Hokusai.
-
E.
Taikon
Taikon is a Romani Swedish family name most prominently associated with activist and silversmith Rosa Taikon and her relatives.
- 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_69ca835df7e08190ac875664cca8f9ca |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5dfa9d6c81908c4c6b3a6f84f67d |
completed | March 31, 2026, 11:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cf4354a4c081908c338db408694abf |
completed | April 3, 2026, 4:34 a.m. |
Created at: March 30, 2026, 6:40 p.m.