Triple
T24164643
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sedleigh |
E598936
|
entity |
| Predicate | relatedFictionalInstitution |
P9446
|
FINISHED |
| Object |
Wrykyn School
Wrykyn School is a fictional English public school created by P. G. Wodehouse and featured in several of his early school stories.
|
E1620468
|
NE FINISHED |
How this triple was built (3 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]
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Wrykyn School Triple: [Sedleigh, relatedFictionalInstitution, Wrykyn School]
Generated description
Wrykyn School is a fictional English public school created by P. G. Wodehouse and featured in several of his early school stories.
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 (6 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. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0fad37a744819094e0b4f2cbbfa330 |
completed | May 22, 2026, 1:11 a.m. |
| NEDg | Description generation | batch_6a0fae4aa5e08190aa6dbcbd7cedcbdc |
completed | May 22, 2026, 1:15 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0faee66d088190aa2b09143548b11b |
completed | May 22, 2026, 1:18 a.m. |
| PD | Predicate disambiguation | batch_69f1c42f942c8190b103ff29a60fef34 |
completed | April 29, 2026, 8:41 a.m. |
Created at: April 17, 2026, 11:32 p.m.