Triple
T4192134
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Blink |
E89059
|
entity |
| Predicate | guestCast |
P45889
|
FINISHED |
| Object |
Tensei Kono
Tensei Kono is a voice actor known for his guest appearance in the anime series "Blink."
|
E420311
|
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: Tensei Kono | Statement: [Blink, guestCast, Tensei Kono]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tensei Kono Context triple: [Blink, guestCast, Tensei Kono]
-
A.
Shinsekai
Shinsekai is a retro entertainment district in Osaka, Japan, known for its nostalgic Showa-era atmosphere, street food, and neon-lit nightlife.
-
B.
Kigensetsu
Kigensetsu was a pre-World War II Japanese national holiday that celebrated the mythical founding of Japan and the divine origins of the emperor.
-
C.
Kakushōkaku
Kakushōkaku is a historic Japanese-style residence located within Yokohama’s Sankeien Garden, known for its traditional architecture and scenic views over the landscaped grounds.
-
D.
Hieda no Are
Hieda no Are was a Japanese court reciter traditionally credited with memorizing the oral histories that formed the basis of the early 8th-century chronicle Kojiki.
-
E.
Oreshura
Oreshura is a Japanese romantic comedy light novel and anime series that follows a high school boy roped into a fake relationship with a popular girl to fend off unwanted romantic attention.
- 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: Tensei Kono Triple: [Blink, guestCast, Tensei Kono]
Generated description
Tensei Kono is a voice actor known for his guest appearance in the anime series "Blink."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Tensei Kono Target entity description: Tensei Kono is a voice actor known for his guest appearance in the anime series "Blink."
-
A.
Shinsekai
Shinsekai is a retro entertainment district in Osaka, Japan, known for its nostalgic Showa-era atmosphere, street food, and neon-lit nightlife.
-
B.
Kigensetsu
Kigensetsu was a pre-World War II Japanese national holiday that celebrated the mythical founding of Japan and the divine origins of the emperor.
-
C.
Kakushōkaku
Kakushōkaku is a historic Japanese-style residence located within Yokohama’s Sankeien Garden, known for its traditional architecture and scenic views over the landscaped grounds.
-
D.
Hieda no Are
Hieda no Are was a Japanese court reciter traditionally credited with memorizing the oral histories that formed the basis of the early 8th-century chronicle Kojiki.
-
E.
Oreshura
Oreshura is a Japanese romantic comedy light novel and anime series that follows a high school boy roped into a fake relationship with a popular girl to fend off unwanted romantic attention.
- 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_69aed9569a4481908b6c1fcec2a11e21 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69af0b2db368819080c1d652b4acfd0c |
completed | March 9, 2026, 6:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b58a08bb6881909bdd7643626e1a64 |
completed | March 14, 2026, 4:17 p.m. |
| NEDg | Description generation | batch_69b58a9497b88190a46afd8b1996fed9 |
completed | March 14, 2026, 4:19 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b58b26e4208190b4ec30a3b635194b |
completed | March 14, 2026, 4:21 p.m. |
Created at: March 9, 2026, 3:46 p.m.