Triple
T9002001
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nisekoi |
E215057
|
entity |
| Predicate | hasSpinOff |
P7226
|
FINISHED |
| Object | Nisekoi: Urabana |
E215057
|
NE FINISHED |
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: Nisekoi: Urabana | Statement: [Nisekoi, hasSpinOff, Nisekoi: Urabana]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nisekoi: Urabana Context triple: [Nisekoi, hasSpinOff, Nisekoi: Urabana]
-
A.
Nisekoi
chosen
Nisekoi is a romantic comedy anime and manga series that follows a high school boy forced into a fake relationship with a yakuza boss’s daughter while searching for his childhood promise girl.
-
B.
Aoi no Ue
Aoi no Ue is a noblewoman and the first principal wife of Prince Genji in the classic Japanese literary work "The Tale of Genji."
-
C.
Nozarashi Kikō
Nozarashi Kikō is a travel diary by the Japanese haiku master Matsuo Bashō that blends prose and verse to chronicle his poetic journey through the countryside.
-
D.
Aishō
Aishō is a town in Shiga Prefecture, Japan, known for its rural character and historical sites.
-
E.
Oi no Kobumi
Oi no Kobumi is a travel diary by the renowned Japanese haiku poet Matsuo Bashō, recording his later journeys and reflections in prose and verse.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69ca83a12d648190b1e4fe11e8a31890 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc6956a6e08190bd3853a7c1c130eb |
completed | April 1, 2026, 12:39 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cfd0ddb1648190a50f8877218d9883 |
completed | April 3, 2026, 2:38 p.m. |
Created at: March 30, 2026, 7:05 p.m.