Triple

T24281381
Position Surface form Disambiguated ID Type / Status
Subject Nebraska state court system E605548 entity
Predicate trialCourtLevel P9881 FINISHED
Object Nebraska county courts
Nebraska county courts are local-level courts in Nebraska that handle minor civil and criminal cases, traffic violations, small claims, and preliminary hearings within the state’s judicial system.
E1632113 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: Nebraska county courts | Statement: [Nebraska state court system, trialCourtLevel, Nebraska county 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: Nebraska county courts
Triple: [Nebraska state court system, trialCourtLevel, Nebraska county courts]
Generated description
Nebraska county courts are local-level courts in Nebraska that handle minor civil and criminal cases, traffic violations, small claims, and preliminary hearings within the state’s judicial system.

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_69e295480d0c8190846fc3c2e2da1d4c completed April 17, 2026, 8:17 p.m.
NER Named-entity recognition batch_69f28f5227888190b1713af150fa30a1 completed April 29, 2026, 11:08 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0fd64c4fc8819087e1f4cd382c0519 completed May 22, 2026, 4:06 a.m.
NEDg Description generation batch_6a0fd920292081909f7e29b638193a8f completed May 22, 2026, 4:18 a.m.
NED2 Entity disambiguation (via description) batch_6a0fda17b2a88190b8b766505be50965 completed May 22, 2026, 4:22 a.m.
Created at: April 18, 2026, 12:08 a.m.