Triple

T30902062
Position Surface form Disambiguated ID Type / Status
Subject Blytheville School District E787196 entity
Predicate hasSchool P113 FINISHED
Object Blytheville Elementary School
Blytheville Elementary School is a public primary school serving early-grade students in the Blytheville School District in Arkansas.
E1939890 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: Blytheville Elementary School | Statement: [Blytheville School District, hasSchool, Blytheville Elementary 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: Blytheville Elementary School
Triple: [Blytheville School District, hasSchool, Blytheville Elementary School]
Generated description
Blytheville Elementary School is a public primary school serving early-grade students in the Blytheville School District in Arkansas.

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_69f224bcbcb48190836df847424e4057 completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f69240a6cc81908c9eca921a675184 completed May 3, 2026, 12:09 a.m.
NED1 Entity disambiguation (via context triple) batch_6a28fba07ed8819096aa282c77c559b8 completed June 10, 2026, 5:52 a.m.
NEDg Description generation batch_6a28fcc827048190b461e0a477a0c3bf completed June 10, 2026, 5:57 a.m.
NED2 Entity disambiguation (via description) batch_6a28fd3b66108190b86217163a2e4e11 completed June 10, 2026, 5:59 a.m.
Created at: April 29, 2026, 8:50 p.m.