Triple
T8132260
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Glynco, Georgia |
E189878
|
entity |
| Predicate | lawEnforcementTrainingFor |
P40765
|
FINISHED |
| Object | federal law enforcement officers |
—
|
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: federal law enforcement officers | Statement: [Glynco, Georgia, lawEnforcementTrainingFor, federal law enforcement officers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: lawEnforcementTrainingFor Context triple: [Glynco, Georgia, lawEnforcementTrainingFor, federal law enforcement officers]
-
A.
lawEnforcementCertification
Indicates that an entity has been officially certified or authorized to perform law enforcement duties.
-
B.
typeOfLawEnforcement
Indicates that one entity is a specific kind or category of law enforcement associated with another entity.
-
C.
providesTrainingFor
chosen
Indicates that one entity delivers or conducts training activities intended to develop the skills or knowledge of another entity.
-
D.
lawEnforcementFunction
Indicates that an entity performs, is responsible for, or is associated with official law enforcement duties or activities.
-
E.
lawEnforcementLabel
Indicates that an entity has been designated, tagged, or classified by a law enforcement authority for monitoring, identification, or investigative purposes.
- 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_69ca82bcb4848190a9a9d036ad768642 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb4c4c2e388190b86854f8b1765e61 |
completed | March 31, 2026, 4:23 a.m. |
| PD | Predicate disambiguation | batch_69cb3696379c8190a20965e59ed8f370 |
completed | March 31, 2026, 2:51 a.m. |
Created at: March 30, 2026, 5:35 p.m.