Triple
T8076980
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Taguchi Tomorowo |
E188516
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
Tomorowo
Tomorowo is a Japanese actor and musician known for his eccentric roles in film and television as well as his work in the rock band Tetsu no Koil.
|
E710370
|
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: Tomorowo | Statement: [Taguchi Tomorowo, givenName, Tomorowo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tomorowo Context triple: [Taguchi Tomorowo, givenName, Tomorowo]
-
A.
Tomonori
Tomonori is a Japanese masculine given name used by various notable individuals in fields such as sports and entertainment.
-
B.
Takeno
Takeno was a former town in Hyōgo Prefecture, Japan, that became part of the expanded city of Toyooka following a municipal merger.
-
C.
Tomoyuki
Tomoyuki is a Japanese masculine given name borne by various notable figures in fields such as the military, arts, and entertainment.
-
D.
Tomomi
Tomomi is a Japanese given name that can be used for people of any gender.
-
E.
Warekena
The Warekena are an Indigenous people of the Amazon region, primarily living along rivers in Brazil and Venezuela, known for their distinct Arawakan language and traditional riverine lifestyle.
- 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: Tomorowo Triple: [Taguchi Tomorowo, givenName, Tomorowo]
Generated description
Tomorowo is a Japanese actor and musician known for his eccentric roles in film and television as well as his work in the rock band Tetsu no Koil.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Tomorowo Target entity description: Tomorowo is a Japanese actor and musician known for his eccentric roles in film and television as well as his work in the rock band Tetsu no Koil.
-
A.
Tomonori
Tomonori is a Japanese masculine given name used by various notable individuals in fields such as sports and entertainment.
-
B.
Takeno
Takeno was a former town in Hyōgo Prefecture, Japan, that became part of the expanded city of Toyooka following a municipal merger.
-
C.
Tomoyuki
Tomoyuki is a Japanese masculine given name borne by various notable figures in fields such as the military, arts, and entertainment.
-
D.
Tomomi
Tomomi is a Japanese given name that can be used for people of any gender.
-
E.
Warekena
The Warekena are an Indigenous people of the Amazon region, primarily living along rivers in Brazil and Venezuela, known for their distinct Arawakan language and traditional riverine lifestyle.
- 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_69ca82b50c708190863f661d438e68df |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb40a184488190b19ef7066f0f5057 |
completed | March 31, 2026, 3:33 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cc63f3f6848190a719b8a9605218ee |
completed | April 1, 2026, 12:16 a.m. |
| NEDg | Description generation | batch_69cc651d340c819089306bac7110f57a |
completed | April 1, 2026, 12:21 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69cc666ecc04819092ee4cc035dde627 |
completed | April 1, 2026, 12:27 a.m. |
Created at: March 30, 2026, 5:28 p.m.