Triple
T30343337
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Saekano: How to Raise a Boring Girlfriend |
E771811
|
entity |
| Predicate | lightNovelMainImprintRunEndYear |
P170201
|
FINISHED |
| Object | 2017 |
—
|
LITERAL 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: 2017 | Statement: [Saekano: How to Raise a Boring Girlfriend, lightNovelMainImprintRunEndYear, 2017]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: lightNovelMainImprintRunEndYear Context triple: [Saekano: How to Raise a Boring Girlfriend, lightNovelMainImprintRunEndYear, 2017]
-
A.
lightNovelLabel
Indicates that a work is labeled or classified as a light novel.
-
B.
lightNovelMagazine
Indicates that a light novel is published in or associated with a particular magazine.
-
C.
lightNovelPublisherCountry
Indicates the country in which the publisher of a given light novel is based.
-
D.
lightNovelDemographic
Indicates the target audience demographic for a given light novel.
-
E.
lightNovelVolumesCount
Indicates the number of volumes that exist for a given light novel.
- F. None of above. chosen
Provenance (4 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_69f68b121eac81909e90416207bc1157 |
completed | May 2, 2026, 11:38 p.m. |
| PD | Predicate disambiguation | batch_69f6860def1c81909d79e1f088c4b5e5 |
completed | May 2, 2026, 11:17 p.m. |
| PDg | Predicate description generation | batch_69f68a160374819084d720985f800dfc |
completed | May 2, 2026, 11:34 p.m. |
Created at: April 29, 2026, 7:55 p.m.