Triple
T12239581
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ise City |
E291692
|
entity |
| Predicate | hasTourismAttraction |
P5121
|
FINISHED |
| Object | Okage-yokocho |
E633360
|
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: Okage-yokocho | Statement: [Ise City, hasTourismAttraction, Okage-yokocho]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Okage-yokocho Context triple: [Ise City, hasTourismAttraction, Okage-yokocho]
-
A.
Okage Yokocho
chosen
Okage Yokocho is a traditional-style shopping and dining district in Ise, Japan, designed to recreate the atmosphere of the Edo and Meiji periods near the Ise Grand Shrine.
-
B.
Nonbei Yokocho
Nonbei Yokocho is a narrow, atmospheric alleyway in Tokyo famed for its tiny, traditional bars and izakayas that evoke the city’s postwar drinking culture.
-
C.
Kanramachi
Kanramachi is a Japanese town known for its cultural and municipal partnership with the Italian town of Certaldo.
-
D.
Sakuragaokacho
Sakuragaokacho is a neighborhood in Tokyo’s Shibuya ward known for its urban atmosphere and proximity to Shibuya Station.
-
E.
Ameya-Yokochō
Ameya-Yokochō is a bustling open-air market street in Tokyo known for its dense concentration of shops, food stalls, and bargain goods.
- 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_69d6ab67950c8190be08450a06228c4b |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d91cb45340819093365f8efdf85f75 |
completed | April 10, 2026, 3:52 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f61e5ff68c81909d2796b24dd055f4 |
completed | May 2, 2026, 3:55 p.m. |
Created at: April 8, 2026, 9:51 p.m.