Triple

T29703875
Position Surface form Disambiguated ID Type / Status
Subject Vernon, Alabama E751571 entity
Predicate hasPublicSchoolSystem P226 FINISHED
Object Lamar County School District
Lamar County School District is the public school system serving students in and around Vernon and the broader Lamar County area in Alabama.
E1879225 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: Lamar County School District | Statement: [Vernon, Alabama, hasPublicSchoolSystem, Lamar County School District]
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: Lamar County School District
Triple: [Vernon, Alabama, hasPublicSchoolSystem, Lamar County School District]
Generated description
Lamar County School District is the public school system serving students in and around Vernon and the broader Lamar County area in Alabama.

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_69f0d6266f8481909e70bb41cda18587 completed April 28, 2026, 3:45 p.m.
NER Named-entity recognition batch_69f672b6ba408190a02e828fd1b62df7 completed May 2, 2026, 9:55 p.m.
NED1 Entity disambiguation (via context triple) batch_6a267ed472e48190ac42f2b04573abf9 completed June 8, 2026, 8:35 a.m.
NEDg Description generation batch_6a2682d4e42c819094c9b078d9d8f0da completed June 8, 2026, 8:52 a.m.
NED2 Entity disambiguation (via description) batch_6a2688794bfc8190b8d87b429f41981f completed June 8, 2026, 9:16 a.m.
Created at: April 28, 2026, 7:26 p.m.