Triple
T30349781
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ore no Kanojo to Osananajimi ga Shuraba Sugiru |
E771960
|
entity |
| Predicate | mainFemaleLead |
P166775
|
FINISHED |
| Object | Masuzu Natsukawa |
—
|
NE NERFINISHED |
How this triple was built (2 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: Masuzu Natsukawa | Statement: [Ore no Kanojo to Osananajimi ga Shuraba Sugiru, mainFemaleLead, Masuzu Natsukawa]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mainFemaleLead Context triple: [Ore no Kanojo to Osananajimi ga Shuraba Sugiru, mainFemaleLead, Masuzu Natsukawa]
-
A.
femaleLeadCharacterStatus
Indicates the narrative or role status assigned to a female lead character within a story or production.
-
B.
mainFemaleStar
chosen
Indicates that the referenced entity serves as the primary or leading female performer in a work or production.
-
C.
numberOfMainFemaleLeadsInWork
Indicates the number of primary female lead characters that appear in a given work.
-
D.
femaleProtagonistName
Indicates that the specified name belongs to a female character who serves as the main protagonist in a narrative.
-
E.
hasLeadCharacterGender
Indicates that the primary or lead character in a work has a specified gender.
- F. None of above.
Provenance (3 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_69f2248b9a208190bc3e6804acd5afd6 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f6820b4b8c81908f5bbae956565ec0 |
completed | May 2, 2026, 11 p.m. |
| PD | Predicate disambiguation | batch_69f678d019fc8190913662cd2f87b857 |
completed | May 2, 2026, 10:21 p.m. |
Created at: April 29, 2026, 7:56 p.m.