Triple
T610681
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hokkaido |
E12089
|
entity |
| Predicate | hasSkiResort |
P1981
|
FINISHED |
| Object |
Furano
Furano is a popular town in central Hokkaido, Japan, known for its scenic ski slopes in winter and vibrant lavender fields in summer.
|
E95894
|
NE FINISHED |
How this triple was built (4 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: [Hokkaido, hasSkiResort, Furano]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Furano Context triple: [Hokkaido, hasSkiResort, Furano]
-
A.
Daikanyama
Daikanyama is a trendy, upscale neighborhood in Tokyo known for its stylish boutiques, cafes, and relaxed, residential atmosphere.
-
B.
Muroran
Muroran is an industrial port city in southern Hokkaido, Japan, known for its steel industry and scenic coastal landscapes.
-
C.
Chitose
Chitose is a city in Hokkaido, Japan, known as the gateway to the region through New Chitose Airport and for its proximity to Lake Shikotsu and surrounding natural scenery.
-
D.
Kitami
Kitami is a city in northeastern Hokkaido, Japan, known for its cold winters, onion production, and proximity to the Okhotsk Sea.
-
E.
Niseko
Niseko is a renowned ski resort area in northern Japan famous for its abundant light powder snow, extensive slopes, and vibrant international winter sports scene.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Furano Triple: [Hokkaido, hasSkiResort, Furano]
Generated description
Furano is a popular town in central Hokkaido, Japan, known for its scenic ski slopes in winter and vibrant lavender fields in summer.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Furano Target entity description: Furano is a popular town in central Hokkaido, Japan, known for its scenic ski slopes in winter and vibrant lavender fields in summer.
-
A.
Daikanyama
Daikanyama is a trendy, upscale neighborhood in Tokyo known for its stylish boutiques, cafes, and relaxed, residential atmosphere.
-
B.
Muroran
Muroran is an industrial port city in southern Hokkaido, Japan, known for its steel industry and scenic coastal landscapes.
-
C.
Chitose
Chitose is a city in Hokkaido, Japan, known as the gateway to the region through New Chitose Airport and for its proximity to Lake Shikotsu and surrounding natural scenery.
-
D.
Kitami
Kitami is a city in northeastern Hokkaido, Japan, known for its cold winters, onion production, and proximity to the Okhotsk Sea.
-
E.
Niseko
Niseko is a renowned ski resort area in northern Japan famous for its abundant light powder snow, extensive slopes, and vibrant international winter sports scene.
- F. None of above. chosen
Provenance (5 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_69a493309df48190a327f748e88049a6 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a49df7c088819082eb70de4f0f4fbf |
completed | March 1, 2026, 8:13 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a76d69ade481909322f5f28f0050e4 |
completed | March 3, 2026, 11:23 p.m. |
| NEDg | Description generation | batch_69a78257f9988190a04b8d764d820194 |
completed | March 4, 2026, 12:52 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69a78337cd4c8190bce8a0716a6e85e4 |
completed | March 4, 2026, 12:56 a.m. |
Created at: March 1, 2026, 7:35 p.m.