Triple
T7851979
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shōnan |
E182077
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object |
Fujisawa
Fujisawa is a coastal city in Kanagawa Prefecture, Japan, known for its beaches, proximity to Enoshima Island, and role as a popular Shōnan resort and commuter hub.
|
E945443
|
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: Fujisawa | Statement: [Shōnan, hasPart, Fujisawa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Fujisawa Context triple: [Shōnan, hasPart, Fujisawa]
-
A.
Fujisawa
Fujisawa is a Japanese surname borne by various notable individuals in fields such as business, politics, and the arts.
-
B.
Akishima
Akishima is a city in western Tokyo, Japan, known as part of the Tama area and characterized by its residential neighborhoods and light industry.
-
C.
Sagamihara
Sagamihara is a major city in Kanagawa Prefecture, Japan, known as a residential and industrial hub within the Greater Tokyo metropolitan area.
-
D.
Moriguchi
Moriguchi is a city in Japan’s Kansai region that forms part of the Osaka metropolitan area and serves as a residential and commercial hub.
-
E.
Fuji City
Fuji City is an industrial city in Shizuoka Prefecture, Japan, known for its paper manufacturing industry and views of nearby Mount Fuji.
- 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: Fujisawa Triple: [Shōnan, hasPart, Fujisawa]
Generated description
Fujisawa is a coastal city in Kanagawa Prefecture, Japan, known for its beaches, proximity to Enoshima Island, and role as a popular Shōnan resort and commuter hub.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Fujisawa Target entity description: Fujisawa is a coastal city in Kanagawa Prefecture, Japan, known for its beaches, proximity to Enoshima Island, and role as a popular Shōnan resort and commuter hub.
-
A.
Fujisawa
Fujisawa is a Japanese surname borne by various notable individuals in fields such as business, politics, and the arts.
-
B.
Akishima
Akishima is a city in western Tokyo, Japan, known as part of the Tama area and characterized by its residential neighborhoods and light industry.
-
C.
Sagamihara
Sagamihara is a major city in Kanagawa Prefecture, Japan, known as a residential and industrial hub within the Greater Tokyo metropolitan area.
-
D.
Moriguchi
Moriguchi is a city in Japan’s Kansai region that forms part of the Osaka metropolitan area and serves as a residential and commercial hub.
-
E.
Fuji City
Fuji City is an industrial city in Shizuoka Prefecture, Japan, known for its paper manufacturing industry and views of nearby Mount Fuji.
- 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_69ca82869ee08190b8f9040dbc2c0467 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb18ec48548190960bd564a60effa8 |
completed | March 31, 2026, 12:44 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f08ec96fe88190b791e6f50f39173f |
completed | April 28, 2026, 10:41 a.m. |
| NEDg | Description generation | batch_69f0bd36673881908530b68e496c3d2e |
completed | April 28, 2026, 1:59 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f0eec1f5d081908624fe2a93995fe5 |
completed | April 28, 2026, 5:30 p.m. |
Created at: March 30, 2026, 4:51 p.m.