Triple
T34660622
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hazzard County, Georgia |
E890095
|
entity |
| Predicate | hasFictionalJail |
P57043
|
FINISHED |
| Object | Hazzard County Jail |
—
|
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: Hazzard County Jail | Statement: [Hazzard County, Georgia, hasFictionalJail, Hazzard County Jail]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFictionalJail Context triple: [Hazzard County, Georgia, hasFictionalJail, Hazzard County Jail]
-
A.
hasJail
Indicates that one entity possesses, operates, or is associated with a jail or detention facility.
-
B.
fictionalPrisonName
chosen
Indicates that an entity is identified by the name of a fictional prison.
-
C.
hasPrison
Indicates that one entity possesses, contains, or is the location of a prison associated with another entity.
-
D.
fictionalPrisoner
Indicates that an entity is portrayed as a prisoner within a fictional or narrative context.
-
E.
hasBeenImprisonedBy
Indicates that one entity has been confined or incarcerated under the authority or control of another entity.
- 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_69f349d906bc8190b2efd9eff237d94b |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69ff878f41888190bcb3bc41ad26081a |
completed | May 9, 2026, 7:14 p.m. |
| PD | Predicate disambiguation | batch_69ff854082d88190aad3bfedf05e849f |
completed | May 9, 2026, 7:04 p.m. |
Created at: May 1, 2026, 2:04 a.m.