Triple
T10297019
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Setagaya |
E241517
|
entity |
| Predicate | hasPark |
P105
|
FINISHED |
| Object | Setagaya Park |
E311728
|
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: Setagaya Park | Statement: [Setagaya, hasPark, Setagaya Park]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Setagaya Park Context triple: [Setagaya, hasPark, Setagaya Park]
-
A.
Setagaya Park
chosen
Setagaya Park is a public green space in Tokyo’s Setagaya ward, known for its recreational facilities and local community use.
-
B.
Maruyama Park
Maruyama Park is a popular public park in Sapporo, Japan, known for its cherry blossoms, sports facilities, and proximity to Hokkaido Shrine and Mount Maruyama.
-
C.
Maruyama Park
Maruyama Park is a famous public park in Kyoto, Japan, especially known for its cherry blossoms and traditional atmosphere.
-
D.
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.
-
E.
Ueno Park
Ueno Park is a large public park in Tokyo famous for its cherry blossoms, cultural institutions like museums and a zoo, and historic temples and shrines.
- 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_69d381aaafc08190af475ef58dc16aba |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d2ebd258819099fadddcd13099fc |
completed | April 7, 2026, 9:48 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d71d2cc9c48190bc36f6a4f8144b7f |
completed | April 9, 2026, 3:29 a.m. |
Created at: April 6, 2026, 11:43 a.m.