Triple
T28672584
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Castle County Sheriff’s Department |
E725767
|
entity |
| Predicate | appearsInStateInFiction |
P13811
|
FINISHED |
| Object | Maine |
—
|
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: Maine | Statement: [Castle County Sheriff’s Department, appearsInStateInFiction, Maine]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: appearsInStateInFiction Context triple: [Castle County Sheriff’s Department, appearsInStateInFiction, Maine]
-
A.
stateInFiction
chosen
Indicates that a particular state or condition exists within a fictional context or narrative world rather than in real-world actuality.
-
B.
appearsIn
Indicates that an entity is present, featured, or occurs within a particular context, work, or medium.
-
C.
livesInFiction
Indicates that one entity exists or resides within the fictional world or narrative setting created by another entity.
-
D.
hasPlaceInFiction
Indicates that a fictional work or element is associated with, set in, or takes place within a particular fictional location or setting.
-
E.
usedInFictionalWork
Indicates that something (such as a concept, object, or character) appears or is employed within a specific fictional work.
- 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_69f01d85be388190b669a0e401e2f2c4 |
completed | April 28, 2026, 2:37 a.m. |
| NER | Named-entity recognition | batch_69f739a638748190808e7a2930dce16e |
completed | May 3, 2026, 12:03 p.m. |
| PD | Predicate disambiguation | batch_69f732f2dc6c8190a4e86da98cc5eb05 |
completed | May 3, 2026, 11:35 a.m. |
Created at: April 28, 2026, 5:04 a.m.