Triple
T15884499
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Miyazaki Airport |
E385155
|
entity |
| Predicate | serves |
P98
|
FINISHED |
| Object | Miyazaki |
E76478
|
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: Miyazaki | Statement: [Miyazaki Airport, serves, Miyazaki]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Miyazaki Context triple: [Miyazaki Airport, serves, Miyazaki]
-
A.
Miyazaki
chosen
Miyazaki is a coastal city on Japan’s Kyushu Island known for its mild climate, beaches, and nearby scenic attractions such as Aoshima Island.
-
B.
Miyazaki
Miyazaki is a residential and commercial district within Nishi Ward of Yokohama, Japan.
-
C.
Gifu
Gifu is a city in central Japan that serves as the capital of Gifu Prefecture, known for its historic cormorant fishing on the Nagara River and its strategic location in the Chūbu region.
-
D.
Shinkawa
Shinkawa is a district within Chūō ward in central Tokyo, Japan, known for its mix of commercial buildings, offices, and residential areas near the Sumida River.
-
E.
Nanyō
Nanyō is a city in Yamagata Prefecture, Japan, known for its hot springs, cherry orchards, and traditional festivals.
- 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_69d86da5b800819083a31be937d738b0 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e1561997bc8190a40e7d68defbbddd |
completed | April 16, 2026, 9:35 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffb04598e0819094274868941195b9 |
completed | May 9, 2026, 10:08 p.m. |
Created at: April 10, 2026, 4:51 a.m.