Triple
T17986672
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mount Bandai |
E430252
|
entity |
| Predicate | nearestCity |
P350
|
FINISHED |
| Object |
Inawashiro
Inawashiro is a town in Fukushima Prefecture, Japan, known for Lake Inawashiro, scenic views of Mount Bandai, and its popular ski and hot spring resorts.
|
E1496738
|
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: Inawashiro | Statement: [Mount Bandai, nearestCity, Inawashiro]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Inawashiro Context triple: [Mount Bandai, nearestCity, Inawashiro]
-
A.
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.
-
B.
Yonashiro
Yonashiro was a former town in Okinawa Prefecture, Japan, that later became part of the city of Uruma through municipal merger.
-
C.
Ishibashi
Ishibashi is a Japanese surname associated with various notable families and individuals in Japan.
-
D.
Inagawa
Inagawa is a town in Hyōgo Prefecture, Japan, known for its suburban residential areas and natural surroundings in the Inagawa River basin.
-
E.
Takizawa
Takizawa is a city in northeastern Japan known for its rural landscapes and proximity to the regional center of Morioka in Iwate Prefecture.
- 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: Inawashiro Triple: [Mount Bandai, nearestCity, Inawashiro]
Generated description
Inawashiro is a town in Fukushima Prefecture, Japan, known for Lake Inawashiro, scenic views of Mount Bandai, and its popular ski and hot spring resorts.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Inawashiro Target entity description: Inawashiro is a town in Fukushima Prefecture, Japan, known for Lake Inawashiro, scenic views of Mount Bandai, and its popular ski and hot spring resorts.
-
A.
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.
-
B.
Yonashiro
Yonashiro was a former town in Okinawa Prefecture, Japan, that later became part of the city of Uruma through municipal merger.
-
C.
Ishibashi
Ishibashi is a Japanese surname associated with various notable families and individuals in Japan.
-
D.
Inagawa
Inagawa is a town in Hyōgo Prefecture, Japan, known for its suburban residential areas and natural surroundings in the Inagawa River basin.
-
E.
Takizawa
Takizawa is a city in northeastern Japan known for its rural landscapes and proximity to the regional center of Morioka in Iwate Prefecture.
- 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_69d8b90364248190a37381adea932f42 |
completed | April 10, 2026, 8:46 a.m. |
| NER | Named-entity recognition | batch_69e4b29c6d0881909d450d2561d532a6 |
completed | April 19, 2026, 10:46 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0a1dfbebf4819096a54f6232bc075b |
completed | May 17, 2026, 7:58 p.m. |
| NEDg | Description generation | batch_6a0a1ef23b6c8190a0194719c34bb971 |
completed | May 17, 2026, 8:02 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0a1fc13900819098ee66684dfdff95 |
completed | May 17, 2026, 8:06 p.m. |
Created at: April 10, 2026, 10:23 a.m.