Triple
T11233373
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shiba |
E265881
|
entity |
| Predicate | hasLandmark |
P105
|
FINISHED |
| Object | Shiba Park |
E267006
|
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: Shiba Park | Statement: [Shiba, hasLandmark, Shiba Park]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Shiba Park Context triple: [Shiba, hasLandmark, Shiba Park]
-
A.
Shiba Park
chosen
Shiba Park is a historic public park in Tokyo known for its views of Tokyo Tower, temples, and seasonal greenery.
-
B.
Yamashita Park
Yamashita Park is a famous seaside public park in Yokohama, Japan, known for its waterfront promenade, harbor views, and historic landmarks.
-
C.
Tsukisamu Park
Tsukisamu Park is a large public park in Sapporo, Japan, known for its expansive green spaces, sports facilities, and seasonal recreational activities.
-
D.
Nakajima Park
Nakajima Park is a large, scenic urban park in central Sapporo known for its ponds, walking paths, cultural facilities, and seasonal beauty.
-
E.
Oishi Park
Oishi Park is a scenic lakeside park in Japan renowned for its seasonal flower displays and panoramic views of Mount Fuji across Lake Kawaguchi.
- 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_69d6aac656d48190b275efaa7d6074ee |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e903b8ec81909f9c89776d35c650 |
completed | April 9, 2026, 5:59 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e4ad56013481909f931505824e3b42 |
completed | April 19, 2026, 10:24 a.m. |
Created at: April 8, 2026, 9:30 p.m.