Triple
T20767651
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hideaki Ito |
E511139
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object |
MOZU
MOZU is a Japanese crime suspense television drama and film series known for its dark tone, intricate conspiracies, and intense action.
|
E1450010
|
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: MOZU | Statement: [Hideaki Ito, notableWork, MOZU]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: MOZU Context triple: [Hideaki Ito, notableWork, MOZU]
-
A.
Mozasu
Mozasu is a central character in Min Jin Lee's novel "Pachinko," a Korean-Japanese man whose life reflects the struggles and resilience of a marginalized immigrant family across generations.
-
B.
Mojon̄
Mojon̄ is a settlement that served as the administrative capital of the former United Nations Trust Territory of the Pacific Islands in Micronesia.
-
C.
Moza
Moza is a prominent Qatari royal and influential public figure best known as Sheikha Moza bint Nasser, a leading advocate for education, social development, and global philanthropy.
-
D.
Mukō
Mukō is a city in Kyoto Prefecture, Japan, known for its residential character and proximity to the Kyoto metropolitan area.
-
E.
Mashū-ko
Mashū-ko is a caldera lake in Hokkaido, Japan, renowned for its exceptional water clarity and scenic volcanic surroundings.
- 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: MOZU Triple: [Hideaki Ito, notableWork, MOZU]
Generated description
MOZU is a Japanese crime suspense television drama and film series known for its dark tone, intricate conspiracies, and intense action.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: MOZU Target entity description: MOZU is a Japanese crime suspense television drama and film series known for its dark tone, intricate conspiracies, and intense action.
-
A.
Mozasu
Mozasu is a central character in Min Jin Lee's novel "Pachinko," a Korean-Japanese man whose life reflects the struggles and resilience of a marginalized immigrant family across generations.
-
B.
Mojon̄
Mojon̄ is a settlement that served as the administrative capital of the former United Nations Trust Territory of the Pacific Islands in Micronesia.
-
C.
Moza
Moza is a prominent Qatari royal and influential public figure best known as Sheikha Moza bint Nasser, a leading advocate for education, social development, and global philanthropy.
-
D.
Mukō
Mukō is a city in Kyoto Prefecture, Japan, known for its residential character and proximity to the Kyoto metropolitan area.
-
E.
Mashū-ko
Mashū-ko is a caldera lake in Hokkaido, Japan, renowned for its exceptional water clarity and scenic volcanic surroundings.
- 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_69e0b4ca01148190ac018e57e0cab46f |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c24df58c8190b37398353ce4bf24 |
completed | April 21, 2026, 12:18 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a08ef8d27dc8190a6ae623f4bbe452e |
completed | May 16, 2026, 10:28 p.m. |
| NEDg | Description generation | batch_6a08f28a96488190bf80089105facd0b |
completed | May 16, 2026, 10:41 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a08f316e7988190920ec8eeb56e76a2 |
completed | May 16, 2026, 10:43 p.m. |
Created at: April 16, 2026, 12:36 p.m.