Triple
T33103526
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shelbyville |
E847122
|
entity |
| Predicate | hasFireDepartmentInFiction |
P78750
|
FINISHED |
| Object | Shelbyville Fire Department |
—
|
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: Shelbyville Fire Department | Statement: [Shelbyville, hasFireDepartmentInFiction, Shelbyville Fire Department]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFireDepartmentInFiction Context triple: [Shelbyville, hasFireDepartmentInFiction, Shelbyville Fire Department]
-
A.
hasFictionalPoliceDepartment
Indicates that an entity is associated with or features a police department that exists only within a fictional or imaginary context.
-
B.
hasDepartmentInFiction
chosen
Indicates that a fictional work includes or features a specific department as part of its setting or narrative.
-
C.
hasFireServicesFrom
Indicates that one entity receives fire protection or firefighting services from another entity.
-
D.
worksAtFictionalPlace
Indicates that an entity is employed at or associated with performing work in a fictional or imaginary location.
-
E.
hasBranchInFictionalLocation
Indicates that an organization maintains a branch, office, or presence within a fictional or imaginary location.
- 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_69f3495686508190b76bf20fa5e00bf7 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69ff069ec1348190815375c5c9e38404 |
completed | May 9, 2026, 10:04 a.m. |
| PD | Predicate disambiguation | batch_69ff05ba57f88190a45d20f18044e0fb |
completed | May 9, 2026, 10 a.m. |
Created at: May 1, 2026, 1:26 a.m.