Triple

T26239594
Position Surface form Disambiguated ID Type / Status
Subject Tennessee General Sessions Courts E656273 entity
Predicate appealsGoTo P13940 FINISHED
Object Tennessee Criminal Courts
Tennessee Criminal Courts are state-level trial courts in Tennessee that handle serious criminal cases such as felonies and certain misdemeanors, often hearing appeals from lower courts.
E31045 NE 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: Tennessee Criminal Courts | Statement: [Tennessee General Sessions Courts, appealsGoTo, Tennessee Criminal Courts]
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Tennessee Criminal Courts
Triple: [Tennessee General Sessions Courts, appealsGoTo, Tennessee Criminal Courts]
Generated description
Tennessee Criminal Courts are state-level trial courts in Tennessee that handle serious criminal cases such as felonies and certain misdemeanors, often hearing appeals from lower courts.

Provenance (5 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_69ee5b4c59a881909d9ee4fd013fffd5 completed April 26, 2026, 6:37 p.m.
NER Named-entity recognition batch_69f60d8d749881909594e450462bca49 completed May 2, 2026, 2:43 p.m.
NED1 Entity disambiguation (via context triple) batch_6a11859e1cf08190a5294811eb072570 completed May 23, 2026, 10:46 a.m.
NEDg Description generation batch_6a11862050608190bf26431a0fb90b07 completed May 23, 2026, 10:49 a.m.
NED2 Entity disambiguation (via description) batch_6a1186c04c2c8190a5e70c9d9a5cbeb8 completed May 23, 2026, 10:51 a.m.
Created at: April 26, 2026, 9:03 p.m.