Triple
T18584602
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Inuyasha |
E454202
|
entity |
| Predicate | hasCharacter |
P2308
|
FINISHED |
| Object |
Kaede
Kaede is a wise, elderly priestess in the anime and manga series "Inuyasha," known for guiding the main characters with her spiritual knowledge and experience.
|
E1337657
|
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: Kaede | Statement: [Inuyasha, hasCharacter, Kaede]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kaede Context triple: [Inuyasha, hasCharacter, Kaede]
-
A.
Lady Kaede
Lady Kaede is a central noblewoman in Akira Kurosawa’s film "Ran," known for her ruthless cunning and manipulative pursuit of power within a war-torn feudal clan.
-
B.
Shikomori
Shikomori is a Bantu language spoken primarily in the Comoros, serving as one of the main indigenous languages of the islands.
-
C.
Shinobu
Shinobu is a Japanese given name commonly used for both males and females and borne by various notable figures in Japanese culture.
-
D.
Samaru
Samaru is a prominent university town and research hub near Zaria in Kaduna State, Nigeria, best known for hosting the main campus of Ahmadu Bello University.
-
E.
Kaoru
Kaoru is a central character in the later chapters of the classic Japanese novel "The Tale of Genji," known for his gentle nature and complex romantic entanglements.
- 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: Kaede Triple: [Inuyasha, hasCharacter, Kaede]
Generated description
Kaede is a wise, elderly priestess in the anime and manga series "Inuyasha," known for guiding the main characters with her spiritual knowledge and experience.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Kaede Target entity description: Kaede is a wise, elderly priestess in the anime and manga series "Inuyasha," known for guiding the main characters with her spiritual knowledge and experience.
-
A.
Lady Kaede
Lady Kaede is a central noblewoman in Akira Kurosawa’s film "Ran," known for her ruthless cunning and manipulative pursuit of power within a war-torn feudal clan.
-
B.
Shikomori
Shikomori is a Bantu language spoken primarily in the Comoros, serving as one of the main indigenous languages of the islands.
-
C.
Shinobu
Shinobu is a Japanese given name commonly used for both males and females and borne by various notable figures in Japanese culture.
-
D.
Samaru
Samaru is a prominent university town and research hub near Zaria in Kaduna State, Nigeria, best known for hosting the main campus of Ahmadu Bello University.
-
E.
Kaoru
Kaoru is a central character in the later chapters of the classic Japanese novel "The Tale of Genji," known for his gentle nature and complex romantic entanglements.
- 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_69d8d38ae7e081908a98df1251842402 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e545b0dff08190a3be481faec34a3c |
completed | April 19, 2026, 9:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a05233eb5ec8190acb14c9e66b879ff |
completed | May 14, 2026, 1:19 a.m. |
| NEDg | Description generation | batch_6a0524327ebc8190a613c84cff540d59 |
completed | May 14, 2026, 1:24 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0527d674fc81908fe4f90ae667802c |
completed | May 14, 2026, 1:39 a.m. |
Created at: April 10, 2026, 11:44 a.m.