Triple
T14577540
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kuniwo Nakamura |
E342094
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
Kuniwo
Kuniwo is a masculine given name of Japanese origin, notably borne by Palauan politician and former president Kuniwo Nakamura.
|
E1349766
|
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: Kuniwo | Statement: [Kuniwo Nakamura, givenName, Kuniwo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kuniwo Context triple: [Kuniwo Nakamura, givenName, Kuniwo]
-
A.
Totsukawa
Totsukawa is a remote mountainous village in Nara Prefecture, Japan, known for its hot springs, suspension bridges, and scenic river valleys.
-
B.
Iwatsuki
Iwatsuki is a former city in Saitama Prefecture, Japan, now a ward of Saitama City known historically for its traditional doll-making industry.
-
C.
Kamiyama
Kamiyama is a Japanese surname borne by various individuals, including artists, athletes, and public figures.
-
D.
Nonoichi
Nonoichi is a city in Ishikawa Prefecture, Japan, known for its residential character and proximity to the regional hub of Kanazawa.
-
E.
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.
- 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: Kuniwo Triple: [Kuniwo Nakamura, givenName, Kuniwo]
Generated description
Kuniwo is a masculine given name of Japanese origin, notably borne by Palauan politician and former president Kuniwo Nakamura.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Kuniwo Target entity description: Kuniwo is a masculine given name of Japanese origin, notably borne by Palauan politician and former president Kuniwo Nakamura.
-
A.
Totsukawa
Totsukawa is a remote mountainous village in Nara Prefecture, Japan, known for its hot springs, suspension bridges, and scenic river valleys.
-
B.
Iwatsuki
Iwatsuki is a former city in Saitama Prefecture, Japan, now a ward of Saitama City known historically for its traditional doll-making industry.
-
C.
Kamiyama
Kamiyama is a Japanese surname borne by various individuals, including artists, athletes, and public figures.
-
D.
Nonoichi
Nonoichi is a city in Ishikawa Prefecture, Japan, known for its residential character and proximity to the regional hub of Kanazawa.
-
E.
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.
- 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_69d822dcc6248190bed689984bceb0e2 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb3f5ec448190b2ef887fdf7b633e |
completed | April 14, 2026, 9:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0590f57a6c8190b11b43fc79c2956b |
completed | May 14, 2026, 9:08 a.m. |
| NEDg | Description generation | batch_6a0594f351fc8190bbc88900cdafbdde |
completed | May 14, 2026, 9:25 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a05962396e08190bcf4327b9c2b02ee |
completed | May 14, 2026, 9:30 a.m. |
Created at: April 10, 2026, 1:24 a.m.