Triple
T8406539
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shiba-koen |
E198513
|
entity |
| Predicate | contains |
P35
|
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-koen, contains, Shiba Park]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Shiba Park Context triple: [Shiba-koen, contains, 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.
Shukugawa Park
Shukugawa Park is a scenic riverside park in Nishinomiya, Japan, renowned for its cherry blossom-lined paths and seasonal beauty.
-
D.
Tsurumai Park
Tsurumai Park is a historic public park in Nagoya, Japan, known for its cherry blossoms, landscaped grounds, and cultural facilities.
-
E.
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.
- 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_69ca8310df9c8190b25f16161cca3e41 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cb8312941c8190af0b2def0a4e02be |
completed | March 31, 2026, 8:17 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ce4db075c881909083b3384fcde344 |
completed | April 2, 2026, 11:06 a.m. |
Created at: March 30, 2026, 6:05 p.m.