Triple
T30348115
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chichibu, Saitama Prefecture |
E771918
|
entity |
| Predicate | isRealLifeSettingOf |
P81329
|
FINISHED |
| Object | Anohana: The Flower We Saw That Day |
—
|
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: Anohana: The Flower We Saw That Day | Statement: [Chichibu, Saitama Prefecture, isRealLifeSettingOf, Anohana: The Flower We Saw That Day]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isRealLifeSettingOf Context triple: [Chichibu, Saitama Prefecture, isRealLifeSettingOf, Anohana: The Flower We Saw That Day]
-
A.
setInFictionalOrRealLocation
chosen
Indicates that something (such as a story, event, or scene) takes place within a specified location, whether that location is real or fictional.
-
B.
portrayedInSetting
Indicates that an entity is depicted or represented within a particular setting, environment, or context.
-
C.
hasFictionalSettingElement
Indicates that something includes or is associated with a specific element or component of a fictional setting.
-
D.
placeOfSetting
Indicates the location or environment where an event, scene, or situation takes place.
-
E.
isCharacterInSetting
Indicates that a particular character appears or exists within a specified setting or environment.
- 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_69f68209227c81909b613d5bc9426038 |
completed | May 2, 2026, 11 p.m. |
| PD | Predicate disambiguation | batch_69f678ce54b081908c26edfd49e39c60 |
completed | May 2, 2026, 10:21 p.m. |
Created at: April 29, 2026, 7:56 p.m.