Triple
T10687412
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Meguro Ward |
E251913
|
entity |
| Predicate | hasDistrict |
P459
|
FINISHED |
| Object | Jiyugaoka |
E268149
|
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: Jiyugaoka | Statement: [Meguro Ward, hasDistrict, Jiyugaoka]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jiyugaoka Context triple: [Meguro Ward, hasDistrict, Jiyugaoka]
-
A.
Jiyūgaoka
chosen
Jiyūgaoka is a fashionable, laid-back neighborhood in Tokyo known for its boutique shopping streets, cafes, and European-inspired atmosphere.
-
B.
Ueno
Ueno is a major district in Tokyo known for Ueno Park, its museums, zoo, and busy transportation hub.
-
C.
Ueno
Ueno is a town in Japan historically known as the birthplace of the renowned haiku poet Matsuo Bashō.
-
D.
Komagome
Komagome is a residential and commercial neighborhood in Tokyo known for its traditional atmosphere, historic temples, and the renowned Rikugien Garden.
-
E.
Yoyogi Park
Yoyogi Park is one of Tokyo’s largest and most popular urban parks, known for its spacious lawns, seasonal cherry blossoms, and role as a major recreational and cultural gathering spot.
- 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_69d6aa5bd7c08190a816e733b4045c23 |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d6fd19f0f481909eeaa75d17d9c060 |
completed | April 9, 2026, 1:12 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f684c471b88190a4c79d907152b492 |
completed | May 2, 2026, 11:12 p.m. |
Created at: April 8, 2026, 9:10 p.m.