Triple
T10817673
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hakone |
E255274
|
entity |
| Predicate | knownFor |
P22
|
FINISHED |
| Object |
Lake Ashi
Lake Ashi is a scenic crater lake in Japan’s Hakone region, famed for its views of Mount Fuji, hot spring resorts, and sightseeing cruises.
|
E887695
|
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: Lake Ashi | Statement: [Hakone, knownFor, Lake Ashi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lake Ashi Context triple: [Hakone, knownFor, Lake Ashi]
-
A.
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.
-
B.
Lake Shoji
Lake Shoji is one of the Fuji Five Lakes in Japan, known for its tranquil waters and scenic views of Mount Fuji.
-
C.
Onota Lake
Onota Lake is a scenic recreational lake in Pittsfield, Massachusetts, popular for boating, fishing, and lakeside activities in the Berkshires region.
-
D.
Lake Kagawong
Lake Kagawong is a freshwater lake on Manitoulin Island in Ontario, Canada, known for its scenic shoreline, recreational fishing, and nearby Bridal Veil Falls.
-
E.
Lake Toho
Lake Toho is a large, renowned bass-fishing lake located in central Florida near Kissimmee.
- 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: Lake Ashi Triple: [Hakone, knownFor, Lake Ashi]
Generated description
Lake Ashi is a scenic crater lake in Japan’s Hakone region, famed for its views of Mount Fuji, hot spring resorts, and sightseeing cruises.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Lake Ashi Target entity description: Lake Ashi is a scenic crater lake in Japan’s Hakone region, famed for its views of Mount Fuji, hot spring resorts, and sightseeing cruises.
-
A.
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.
-
B.
Lake Shoji
Lake Shoji is one of the Fuji Five Lakes in Japan, known for its tranquil waters and scenic views of Mount Fuji.
-
C.
Onota Lake
Onota Lake is a scenic recreational lake in Pittsfield, Massachusetts, popular for boating, fishing, and lakeside activities in the Berkshires region.
-
D.
Lake Kagawong
Lake Kagawong is a freshwater lake on Manitoulin Island in Ontario, Canada, known for its scenic shoreline, recreational fishing, and nearby Bridal Veil Falls.
-
E.
Lake Toho
Lake Toho is a large, renowned bass-fishing lake located in central Florida near Kissimmee.
- 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_69d6aa8081448190a9324184f2bd1c26 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d7344866f88190be4addb7c8020fce |
completed | April 9, 2026, 5:08 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69de855799748190b51745a198daa8d0 |
completed | April 14, 2026, 6:20 p.m. |
| NEDg | Description generation | batch_69de8955b9d8819086ff98efbff6c7a0 |
completed | April 14, 2026, 6:37 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69de8f4a318c819086559fd53506ab29 |
completed | April 14, 2026, 7:02 p.m. |
Created at: April 8, 2026, 9:18 p.m.