Triple
T15650152
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Comiso Airport |
E376288
|
entity |
| Predicate | nearbyCity |
P350
|
FINISHED |
| Object | Noto |
E127132
|
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: Noto | Statement: [Comiso Airport, nearbyCity, Noto]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Noto Context triple: [Comiso Airport, nearbyCity, Noto]
-
A.
Noto
chosen
Noto is a historic town in southeastern Sicily renowned for its exquisite late Baroque architecture and status as a UNESCO World Heritage Site.
-
B.
Noto
Noto is the alias of German electronic musician and visual artist Alva Noto, known for his minimalist, experimental sound and multimedia installations.
-
C.
Noto
Noto is a historical region on the Noto Peninsula in Ishikawa Prefecture, Japan, known for its scenic coastline, traditional fishing villages, and cultural heritage.
-
D.
Sutoku
Sutoku was a 12th-century Japanese emperor whose abdication and later role in the Hōgen Rebellion made him a legendary figure associated with political turmoil and vengeful spirit lore.
-
E.
Nishio
Nishio is a city in Aichi Prefecture, Japan, known for its high-quality matcha green tea production and traditional Japanese culture.
- 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_69d85cd1564c8190991adda63bfab4b0 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04eeed2d48190a7a8a618d90012d0 |
completed | April 16, 2026, 2:52 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff7568028481908caa1e49541bbcf1 |
completed | May 9, 2026, 5:56 p.m. |
Created at: April 10, 2026, 4:15 a.m.