Triple
T7891497
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ise-Shima National Park |
E183244
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Shima |
E304203
|
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: Shima | Statement: [Ise-Shima National Park, contains, Shima]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Shima Context triple: [Ise-Shima National Park, contains, Shima]
-
A.
Shima
chosen
Shima is a coastal city in central Japan known for its scenic bays, pearl cultivation, and role within the Ise-Shima tourist region.
-
B.
Meijima
Meijima is one of the small islands that make up Japan’s Mukojima Islands group in the Ogasawara (Bonin) archipelago.
-
C.
Yumeshima
Yumeshima is a large artificial island in Osaka, Japan, known for planned large-scale developments including expo and integrated resort projects.
-
D.
Tsukishima
Tsukishima is a man-made island and residential district in Tokyo’s Chūō ward, known for its high-rise apartments and famous monjayaki restaurants.
-
E.
Okishima
Okishima is a small inhabited island located within Japan’s Lake Biwa, known for its traditional fishing community and car-free lifestyle.
- 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_69ca828c474c8190a254d6499871eaff |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb39ee137081908e87e35016c3a176 |
completed | March 31, 2026, 3:05 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d065a63f8c8190a50f814fb70e0e31 |
completed | April 4, 2026, 1:13 a.m. |
Created at: March 30, 2026, 5 p.m.