Triple
T14762113
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kōtō, Tokyo, Japan |
E346890
|
entity |
| Predicate | containsPark |
P22590
|
FINISHED |
| Object | Kiba Park |
E1076977
|
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: Kiba Park | Statement: [Kōtō, Tokyo, Japan, containsPark, Kiba Park]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kiba Park Context triple: [Kōtō, Tokyo, Japan, containsPark, Kiba Park]
-
A.
Kiba Park
chosen
Kiba Park is a large public park in Tokyo known for its open green spaces, sports facilities, and cultural attractions such as the Museum of Contemporary Art Tokyo.
-
B.
Kinshi Park
Kinshi Park is a popular urban green space in Tokyo’s Kinshichō district, known for its cherry blossoms, sports facilities, and views of Tokyo Skytree.
-
C.
Yamashita Park
Yamashita Park is a famous seaside public park in Yokohama, Japan, known for its waterfront promenade, harbor views, and historic landmarks.
-
D.
Seka Park
Seka Park is a large coastal urban park and recreational area in İzmit, Turkey, known for its green spaces, walking paths, and cultural facilities along the Gulf of İzmit.
-
E.
Shiba Park
Shiba Park is a historic public park in Tokyo known for its views of Tokyo Tower, temples, and seasonal greenery.
- 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_69d822e8896c819091169882f9b20486 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69dec7f207dc819088a53f717736a121 |
completed | April 14, 2026, 11:04 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe64f0d948819080cc759ca599503d |
completed | May 8, 2026, 10:34 p.m. |
Created at: April 10, 2026, 1:30 a.m.