Triple
T18436930
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | England (fictional) |
E450415
|
entity |
| Predicate | includesFictionalInstitution |
P71478
|
FINISHED |
| Object | local fair |
—
|
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: local fair | Statement: [England (fictional), includesFictionalInstitution, local fair]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: includesFictionalInstitution Context triple: [England (fictional), includesFictionalInstitution, local fair]
-
A.
hasFictionalSchool
Indicates that an entity is associated with or contains a school that exists only within a fictional or imaginary context.
-
B.
worksForFictionalOrganization
Indicates that an entity is employed by or affiliated as a worker with a fictional organization.
-
C.
hasFictionalEstablishmentType
chosen
Indicates that an establishment is associated with a particular type or category of fictional setting or institution.
-
D.
hasFictionalPub
Indicates that an entity features or includes a fictional pub as part of its content, setting, or structure.
-
E.
hasFictionalMediaOutlet
Indicates that an entity is associated with or features a fictional media outlet (such as an invented TV station, newspaper, or network) within its narrative or 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_69d8d381d6388190a9e94e9c658174e4 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e51c0e04508190bc851a8954ae60e8 |
completed | April 19, 2026, 6:16 p.m. |
| PD | Predicate disambiguation | batch_69e469c943a4819094c8fdc5971ad3a7 |
completed | April 19, 2026, 5:36 a.m. |
Created at: April 10, 2026, 11:29 a.m.