Triple
T12659187
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Noto Province |
E302370
|
entity |
| Predicate | hasPortTown |
P2745
|
FINISHED |
| Object | Nanao |
E1105710
|
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: Nanao | Statement: [Noto Province, hasPortTown, Nanao]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nanao Context triple: [Noto Province, hasPortTown, Nanao]
-
A.
Nanao
chosen
Nanao is a coastal city in Ishikawa Prefecture, Japan, historically known as the political and economic center of the former Noto region.
-
B.
Yokote
Yokote is a city in Akita Prefecture, Japan, known for its heavy snowfall and the annual Yokote Kamakura Snow Festival featuring traditional igloo-like snow huts.
-
C.
Tateyama
Tateyama is a coastal city in southern Chiba Prefecture, Japan, known for its mild climate, beaches, and views of Mount Fuji across Tokyo Bay.
-
D.
Yashio
Yashio is a city in Saitama Prefecture, Japan, located on the outskirts of Tokyo and functioning largely as a residential commuter town.
-
E.
Yashio
Yashio is a district in Tokyo’s Shinagawa Ward, known primarily as a modern waterfront residential and commercial area.
- 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_69d7bded71a88190bb76e2413af9ea66 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d961636db8819099c438b24bcfd866 |
completed | April 10, 2026, 8:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fda8fd6f5081908de9a9e3df28a8ea |
completed | May 8, 2026, 9:12 a.m. |
Created at: April 9, 2026, 5:19 p.m.