Triple
T2316255
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mount Fuji |
E51069
|
entity |
| Predicate | nearCity |
P350
|
FINISHED |
| Object |
Gotemba
Gotemba is a Japanese city in Shizuoka Prefecture known as a gateway to Mount Fuji and a popular base for outdoor activities and outlet shopping.
|
E329286
|
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: Gotemba | Statement: [Mount Fuji, nearCity, Gotemba]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gotemba Context triple: [Mount Fuji, nearCity, Gotemba]
-
A.
Takamikura
Takamikura is the ornate imperial throne used in Kyoto for the enthronement ceremonies of Japanese emperors.
-
B.
Sendagaya
Sendagaya is a neighborhood in Tokyo known for its sports facilities, including the National Stadium, and its proximity to Shinjuku and Harajuku.
-
C.
Shumshu
Shumshu is a small, strategically significant volcanic island at the northern end of the Kuril Islands chain, near the Kamchatka Peninsula.
-
D.
Marunouchi
Marunouchi is a central Tokyo business district known for its concentration of corporate headquarters, upscale offices, and proximity to Tokyo Station and the Imperial Palace.
-
E.
Kamiyama
Kamiyama is a Japanese surname borne by various individuals, including artists, athletes, and public figures.
- 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: Gotemba Triple: [Mount Fuji, nearCity, Gotemba]
Generated description
Gotemba is a Japanese city in Shizuoka Prefecture known as a gateway to Mount Fuji and a popular base for outdoor activities and outlet shopping.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Gotemba Target entity description: Gotemba is a Japanese city in Shizuoka Prefecture known as a gateway to Mount Fuji and a popular base for outdoor activities and outlet shopping.
-
A.
Takamikura
Takamikura is the ornate imperial throne used in Kyoto for the enthronement ceremonies of Japanese emperors.
-
B.
Sendagaya
Sendagaya is a neighborhood in Tokyo known for its sports facilities, including the National Stadium, and its proximity to Shinjuku and Harajuku.
-
C.
Shumshu
Shumshu is a small, strategically significant volcanic island at the northern end of the Kuril Islands chain, near the Kamchatka Peninsula.
-
D.
Marunouchi
Marunouchi is a central Tokyo business district known for its concentration of corporate headquarters, upscale offices, and proximity to Tokyo Station and the Imperial Palace.
-
E.
Kamiyama
Kamiyama is a Japanese surname borne by various individuals, including artists, athletes, and public figures.
- 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_69a88b074b908190ae983dbca7757d88 |
completed | March 4, 2026, 7:41 p.m. |
| NER | Named-entity recognition | batch_69abc61e72508190b335cda2c7fef130 |
completed | March 7, 2026, 6:30 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b20f1577388190bc95b2151af55732 |
completed | March 12, 2026, 12:55 a.m. |
| NEDg | Description generation | batch_69b2131c2d6081908f8586af6dcf153a |
completed | March 12, 2026, 1:13 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b213c46ca08190a1f30dccae09267d |
completed | March 12, 2026, 1:15 a.m. |
Created at: March 4, 2026, 7:49 p.m.