Triple
T13356530
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Naoko |
E318706
|
entity |
| Predicate | closeTo |
P350
|
FINISHED |
| Object |
Kizuki
Kizuki is a pivotal, emotionally fragile character in Haruki Murakami's novel "Norwegian Wood," whose death profoundly shapes the lives of those close to him.
|
E1127392
|
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: Kizuki | Statement: [Naoko, closeTo, Kizuki]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kizuki Context triple: [Naoko, closeTo, Kizuki]
-
A.
Wajima
Wajima is a coastal city in Ishikawa Prefecture, Japan, renowned for its traditional Wajima-nuri lacquerware and historic morning market.
-
B.
Akizuki
Akizuki was a Japanese Akizuki-class destroyer of the Imperial Japanese Navy that served in World War II before being sunk in the Battle off Cape Engaño in 1944.
-
C.
Shimotsuki
Shimotsuki was a Japanese destroyer of the Imperial Japanese Navy that served in World War II before being sunk in late 1944.
-
D.
Ushijima
Ushijima is a Japanese surname borne by various notable individuals, including military figures and fictional characters.
-
E.
Katsuragi
Katsuragi is a city in Japan known for its location in Nara Prefecture and its historical and cultural ties to the ancient Yamato region.
- 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: Kizuki Triple: [Naoko, closeTo, Kizuki]
Generated description
Kizuki is a pivotal, emotionally fragile character in Haruki Murakami's novel "Norwegian Wood," whose death profoundly shapes the lives of those close to him.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Kizuki Target entity description: Kizuki is a pivotal, emotionally fragile character in Haruki Murakami's novel "Norwegian Wood," whose death profoundly shapes the lives of those close to him.
-
A.
Wajima
Wajima is a coastal city in Ishikawa Prefecture, Japan, renowned for its traditional Wajima-nuri lacquerware and historic morning market.
-
B.
Akizuki
Akizuki was a Japanese Akizuki-class destroyer of the Imperial Japanese Navy that served in World War II before being sunk in the Battle off Cape Engaño in 1944.
-
C.
Shimotsuki
Shimotsuki was a Japanese destroyer of the Imperial Japanese Navy that served in World War II before being sunk in late 1944.
-
D.
Ushijima
Ushijima is a Japanese surname borne by various notable individuals, including military figures and fictional characters.
-
E.
Katsuragi
Katsuragi is a city in Japan known for its location in Nara Prefecture and its historical and cultural ties to the ancient Yamato region.
- 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_69d806b7bbac8190b85278c87fa7aff3 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dadcd4cb008190af99c4856e76ac08 |
completed | April 11, 2026, 11:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe729766008190803c1dfef2c8c872 |
completed | May 8, 2026, 11:32 p.m. |
| NEDg | Description generation | batch_69fe73ee0da48190b8909009e0dc517b |
completed | May 8, 2026, 11:38 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69fe748da7948190b7253b9dc09ae9fa |
completed | May 8, 2026, 11:41 p.m. |
Created at: April 9, 2026, 9:32 p.m.