Triple
T28333223
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Claudine à l’école |
E717588
|
entity |
| Predicate | hasFictionalSchoolSetting |
P29320
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Claudine à l’école, hasFictionalSchoolSetting, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFictionalSchoolSetting Context triple: [Claudine à l’école, hasFictionalSchoolSetting, yes]
-
A.
hasFictionalSchool
chosen
Indicates that an entity is associated with or contains a school that exists only within a fictional or imaginary context.
-
B.
hasFictionalSettingElement
Indicates that something includes or is associated with a specific element or component of a fictional setting.
-
C.
associatedWithFictionalSetting
Indicates that an entity has a connection or relevance to a particular fictional setting or universe.
-
D.
operatesInFictionalSetting
Indicates that an entity carries out its activities or functions within a fictional or imaginary setting rather than a real-world context.
-
E.
basedInFictionalSetting
Indicates that an entity’s primary location or setting exists within a fictional or imaginary world rather than the real world.
- 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_69eff6e9a57c8190a69c2c74b5d72119 |
completed | April 27, 2026, 11:53 p.m. |
| NER | Named-entity recognition | batch_69fd32848ea88190a71e6df402bbb30e |
completed | May 8, 2026, 12:47 a.m. |
| PD | Predicate disambiguation | batch_69fd2d7e95588190991d5f21e25155df |
completed | May 8, 2026, 12:25 a.m. |
Created at: April 28, 2026, 12:33 a.m.