Triple
T17123585
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kanda district |
E415529
|
entity |
| Predicate | hasSubarea |
P747
|
FINISHED |
| Object | Kanda-Jimbocho |
—
|
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: Kanda-Jimbocho | Statement: [Kanda district, hasSubarea, Kanda-Jimbocho]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kanda-Jimbocho Context triple: [Kanda district, hasSubarea, Kanda-Jimbocho]
-
A.
Kanda-Jimbocho
chosen
Kanda-Jimbocho is Tokyo’s famed book district, renowned for its dense concentration of secondhand bookstores, publishing houses, and literary culture.
-
B.
Kamitabashi
Kamitabashi is a residential neighborhood located in the Kita ward of Tokyo, Japan.
-
C.
Hamamatsucho
Hamamatsucho is a central Tokyo district and major transportation hub known for its JR and monorail stations providing access to Haneda Airport and nearby business and waterfront areas.
-
D.
Yurakucho
Yurakucho is a lively commercial and entertainment district in central Tokyo known for its shopping complexes, theaters, and atmospheric izakaya alleys beneath the railway tracks.
-
E.
Nishi-Ogikubo
Nishi-Ogikubo is a Tokyo neighborhood known for its laid-back residential atmosphere, vintage and antique shops, and small independent cafes and bars.
- 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_69d886d090cc8190a39cb94992586905 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3e80b7e6881909f7635875549a2f1 |
completed | April 18, 2026, 8:22 p.m. |
Created at: April 10, 2026, 5:36 a.m.