Triple
T19286213
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Semboku |
E482317
|
entity |
| Predicate | knownFor |
P22
|
FINISHED |
| Object | Lake Tazawa |
—
|
NE NERFINISHED |
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: Lake Tazawa | Statement: [Semboku, knownFor, Lake Tazawa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lake Tazawa Context triple: [Semboku, knownFor, Lake Tazawa]
-
A.
Lake Tazawa
chosen
Lake Tazawa is a deep, scenic caldera lake in northern Japan renowned for its clear blue waters and surrounding hot spring resorts.
-
B.
Lake Akimoto
Lake Akimoto is a dammed lake in Fukushima Prefecture, Japan, known as part of the scenic Bandai-kōgen highland lake district formed by the eruption of Mount Bandai.
-
C.
Lake Shoji
Lake Shoji is one of the Fuji Five Lakes in Japan, known for its tranquil waters and scenic views of Mount Fuji.
-
D.
Lake Haruna
Lake Haruna is a scenic crater lake in Gunma Prefecture, Japan, known for its tranquil waters, surrounding volcanic landscapes, and popularity as a recreational and tourist destination.
-
E.
Lake Tōya
Lake Tōya is a nearly circular caldera lake in Hokkaido, Japan, renowned for its clear waters, scenic volcanic surroundings, and hot spring resorts.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8e8cf61b0819096fe3e4107827c4e |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e5fc024a7081909a25d7cc4e048f79 |
completed | April 20, 2026, 10:12 a.m. |
Created at: April 10, 2026, 1:30 p.m.