Triple
T24164643
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sedleigh |
E598936
|
entity |
| Predicate | relatedFictionalInstitution |
P9446
|
FINISHED |
| Object | Wrykyn School |
—
|
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: Wrykyn School | Statement: [Sedleigh, relatedFictionalInstitution, Wrykyn School]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relatedFictionalInstitution Context triple: [Sedleigh, relatedFictionalInstitution, Wrykyn School]
-
A.
relatedInstitution
chosen
Indicates that there is an institutional connection or association between two entities, such as affiliation, partnership, or organizational linkage.
-
B.
hasFictionalEstablishmentType
Indicates that an establishment is associated with a particular type or category of fictional setting or institution.
-
C.
worksForFictionalOrganization
Indicates that an entity is employed by or affiliated as a worker with a fictional organization.
-
D.
associatedInstitution
Indicates that an entity has a formal connection or affiliation with a particular institution.
-
E.
fictionalUniversityAffiliation
Indicates that an entity is affiliated with a university that exists only in a fictional or imaginary context.
- 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_69e288cbd62881909de32ca64a70c17b |
completed | April 17, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69f27c9ddfcc819096697a844b300cce |
completed | April 29, 2026, 9:48 p.m. |
| PD | Predicate disambiguation | batch_69f1c42f942c8190b103ff29a60fef34 |
completed | April 29, 2026, 8:41 a.m. |
Created at: April 17, 2026, 11:32 p.m.