Triple
T10174254
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kappabashi-dori |
E235810
|
entity |
| Predicate | ward |
P21208
|
FINISHED |
| Object | Taito |
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: Taito | Statement: [Kappabashi-dori, ward, Taito]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Taito Context triple: [Kappabashi-dori, ward, Taito]
-
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.
Tunechi
Tunechi is a popular nickname and alter ego of American rapper Lil Wayne, often used to refer to his distinctive persona and musical brand.
-
C.
Touki Bouki
Touki Bouki is a 1973 Senegalese avant-garde road film by Djibril Diop Mambéty, celebrated for its innovative style and critique of postcolonial society.
-
D.
Tapa
Tapa is a town in northern Estonia that serves as a key railway junction and transport hub in the country’s rail network.
-
E.
Tokitarō
Tokitarō was the childhood given name of the renowned Japanese ukiyo-e artist Katsushika Hokusai.
- 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_69ca84d1d5f88190ab878a1021ecff68 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdeca0dc508190916f2a1bbb288192 |
completed | April 2, 2026, 4:12 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d3178844c48190af952ac30a4d6d97 |
completed | April 6, 2026, 2:16 a.m. |
Created at: March 30, 2026, 9:11 p.m.