Triple
T25103135
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | McNairy County, Tennessee |
E628786
|
entity |
| Predicate | hasLawEnforcementHistory |
P167247
|
FINISHED |
| Object | Buford Pusser anti-corruption campaigns in the 1960s |
—
|
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: Buford Pusser anti-corruption campaigns in the 1960s | Statement: [McNairy County, Tennessee, hasLawEnforcementHistory, Buford Pusser anti-corruption campaigns in the 1960s]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLawEnforcementHistory Context triple: [McNairy County, Tennessee, hasLawEnforcementHistory, Buford Pusser anti-corruption campaigns in the 1960s]
-
A.
hasHadCriminalConviction
Indicates that an entity has previously been found guilty of a criminal offense through a legal process.
-
B.
wasArrested
Indicates that an authority detained and took a person into legal custody in connection with a suspected offense.
-
C.
hasFirstConviction
Indicates that an entity has received its first legal conviction for an offense.
-
D.
hasCriminalCharacter
Indicates that an entity possesses traits, behaviors, or a reputation associated with criminal activity or unlawful conduct.
-
E.
criminalRecord
Indicates that an entity has a documented history of criminal offenses or convictions recorded by an authority.
- F. None of above. chosen
Provenance (4 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_69e2ff3071548190b62d1ac237397197 |
completed | April 18, 2026, 3:49 a.m. |
| NER | Named-entity recognition | batch_69f66a6468ec8190a43ed6cd8c797f42 |
completed | May 2, 2026, 9:19 p.m. |
| PD | Predicate disambiguation | batch_69f66598d6008190a7ca8ff80399fd34 |
completed | May 2, 2026, 8:59 p.m. |
| PDg | Predicate description generation | batch_69f6691da93081909deaf680614fc900 |
completed | May 2, 2026, 9:14 p.m. |
Created at: April 18, 2026, 6:26 a.m.