Triple
T16404980
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nagasaki Airport |
E398402
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Omura |
E861192
|
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: Omura | Statement: [Nagasaki Airport, locatedIn, Omura]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Omura Context triple: [Nagasaki Airport, locatedIn, Omura]
-
A.
Omura
chosen
Omura is a coastal city in western Japan known for its proximity to Nagasaki, Omura Bay, and its regional industrial and transportation hubs.
-
B.
Maruim
Maruim is a municipality in the Brazilian state of Sergipe, located along the Sergipe River and known for its historical and regional cultural significance.
-
C.
Omishima
Omishima is a scenic island in Japan’s Seto Inland Sea, known for its cycling route on the Shimanami Kaido, historic Oyamazumi Shrine, and coastal landscapes.
-
D.
Shimamoto
Shimamoto is a town in Osaka Prefecture, Japan, located between Kyoto and Osaka along the Yodo River.
-
E.
Unoshima
Unoshima is a small island located within Lake Kawaguchi, a scenic lake near Mount Fuji in Japan.
- 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_69d87f2950248190bc8ad9b9bebdc8c8 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e327d1f16481909adb19dab86dcc72 |
completed | April 18, 2026, 6:42 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a003c6094e481909aa7402fd17fedae |
completed | May 10, 2026, 8:05 a.m. |
Created at: April 10, 2026, 5:09 a.m.