Triple
T10600983
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hitoshi |
E275744
|
entity |
| Predicate | hasNotableBearer |
P458
|
FINISHED |
| Object |
Hitoshi Takagi
Hitoshi Takagi is a Japanese voice actor best known for voicing the character Totoro in Studio Ghibli’s animated film "My Neighbor Totoro."
|
E1140178
|
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: Hitoshi Takagi | Statement: [Hitoshi, hasNotableBearer, Hitoshi Takagi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hitoshi Takagi Context triple: [Hitoshi, hasNotableBearer, Hitoshi Takagi]
-
A.
Hitoshi Nakajima
Hitoshi Nakajima is a Japanese individual notable enough to be specifically distinguished from others sharing the given name Hitoshi.
-
B.
Hitoshi Saito
Hitoshi Saito was a Japanese judoka and two-time Olympic gold medalist renowned as one of the sport’s dominant heavyweights in the 1980s.
-
C.
Hitoshi Kato
Hitoshi Kato is a Japanese individual notable enough to be specifically distinguished from others sharing the given name Hitoshi.
-
D.
Hitoshi Sato
Hitoshi Sato is a Japanese former professional cyclist known for competing in national and international road racing events.
-
E.
Hitoshi Tamura
Hitoshi Tamura is a Japanese individual notable enough to be specifically distinguished from others sharing the given name Hitoshi.
- 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: Hitoshi Takagi Triple: [Hitoshi, hasNotableBearer, Hitoshi Takagi]
Generated description
Hitoshi Takagi is a Japanese voice actor best known for voicing the character Totoro in Studio Ghibli’s animated film "My Neighbor Totoro."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Hitoshi Takagi Target entity description: Hitoshi Takagi is a Japanese voice actor best known for voicing the character Totoro in Studio Ghibli’s animated film "My Neighbor Totoro."
-
A.
Hitoshi Nakajima
Hitoshi Nakajima is a Japanese individual notable enough to be specifically distinguished from others sharing the given name Hitoshi.
-
B.
Hitoshi Saito
Hitoshi Saito was a Japanese judoka and two-time Olympic gold medalist renowned as one of the sport’s dominant heavyweights in the 1980s.
-
C.
Hitoshi Kato
Hitoshi Kato is a Japanese individual notable enough to be specifically distinguished from others sharing the given name Hitoshi.
-
D.
Hitoshi Sato
Hitoshi Sato is a Japanese former professional cyclist known for competing in national and international road racing events.
-
E.
Hitoshi Tamura
Hitoshi Tamura is a Japanese individual notable enough to be specifically distinguished from others sharing the given name Hitoshi.
- 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_69d6aaf948d88190806cc3a8c47a3fb2 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d6ded52f288190b40288d0acbe009b |
completed | April 8, 2026, 11:03 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69febfcbbf408190a87f471d2732148b |
completed | May 9, 2026, 5:02 a.m. |
| NEDg | Description generation | batch_69fec21c8e1c8190b2a528acabdf2a49 |
completed | May 9, 2026, 5:11 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fec2b612c8819084e4601dfff4ad81 |
completed | May 9, 2026, 5:14 a.m. |
Created at: April 8, 2026, 7:31 p.m.