Triple
T14979478
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Biei |
E373536
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | Furano |
E95894
|
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: Furano | Statement: [Biei, locatedNear, Furano]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Furano Context triple: [Biei, locatedNear, Furano]
-
A.
Furano
chosen
Furano is a popular town in central Hokkaido, Japan, known for its scenic ski slopes in winter and vibrant lavender fields in summer.
-
B.
Towada
Towada is a city in northern Japan known for its proximity to Lake Towada and the scenic Oirase Gorge.
-
C.
Biei
Biei is a picturesque rural town in Hokkaido, Japan, famed for its rolling patchwork hills, flower fields, and scenic landscapes that attract photographers and tourists year-round.
-
D.
Lacco Ameno
Lacco Ameno is a small coastal town on the Italian island of Ischia, known for its thermal spas, picturesque harbor, and distinctive mushroom-shaped rock in the sea.
-
E.
Yonezawa
Yonezawa is a city in southern Yamagata Prefecture, Japan, known for its historic castle town, high-quality Yonezawa beef, and snowy climate.
- 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_69d85ccbbcd48190acb56e7cf104d8ad |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded6fcebf481909f72cab577560d82 |
completed | April 15, 2026, 12:08 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe9dc625888190bf98eecf5f5b6707 |
completed | May 9, 2026, 2:36 a.m. |
Created at: April 10, 2026, 2:51 a.m.