Triple
T21299503
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Uguisudani Station |
E525017
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Taito, Tokyo |
—
|
NE NERFINISHED |
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: Taito, Tokyo | Statement: [Uguisudani Station, locatedIn, Taito, Tokyo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Taito, Tokyo Context triple: [Uguisudani Station, locatedIn, Taito, Tokyo]
-
A.
Taito
Taito is the pseudonym of Tetsuzō, under which he is known for his creative and professional work.
-
B.
Tokyo Round
The Tokyo Round was a major series of multilateral trade negotiations under the General Agreement on Tariffs and Trade (GATT) during the 1970s that aimed to reduce tariffs and address non-tariff barriers to international trade.
-
C.
Taikon
Taikon is a Romani Swedish family name most prominently associated with activist and silversmith Rosa Taikon and her relatives.
-
D.
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.
-
E.
Tokyo Daishoten
Tokyo Daishoten is a prominent year-end Grade 1 dirt horse race in Japan, attracting top-level competitors from across the country and abroad.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b517e6748190850d6f6ddf323d69 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e7385b1c548190b940ded0163ee3ca |
completed | April 21, 2026, 8:42 a.m. |
Created at: April 16, 2026, 4:05 p.m.