Triple

T33181563
Position Surface form Disambiguated ID Type / Status
Subject White County, Georgia E849340 entity
Predicate contains P35 FINISHED
Object White County High School
White County High School is a public secondary school serving students in White County, Georgia, providing comprehensive academic and extracurricular programs for the local community.
E2039523 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: White County High School | Statement: [White County, Georgia, contains, White County High School]
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: White County High School
Triple: [White County, Georgia, contains, White County High School]
Generated description
White County High School is a public secondary school serving students in White County, Georgia, providing comprehensive academic and extracurricular programs for the local community.

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_69f3495d06508190b0b7729982982cea completed April 30, 2026, 12:21 p.m.
NER Named-entity recognition batch_69f6d99dc7108190a4ea556f2a4eb95e completed May 3, 2026, 5:14 a.m.
NED1 Entity disambiguation (via context triple) batch_6a3525cbeef08190bab7af698cbe798d completed June 19, 2026, 11:19 a.m.
NEDg Description generation batch_6a35269b33708190b57524f61a445006 completed June 19, 2026, 11:23 a.m.
NED2 Entity disambiguation (via description) batch_6a352766ac5c8190a15fb9939e4527e6 completed June 19, 2026, 11:26 a.m.
Created at: May 1, 2026, 1:29 a.m.