Triple

T30647005
Position Surface form Disambiguated ID Type / Status
Subject Mascoutah, Illinois E780150 entity
Predicate hasPublicElementarySchool P113 FINISHED
Object Mascoutah Elementary School
Mascoutah Elementary School is a public primary school serving young students in the community of Mascoutah, Illinois.
E1930244 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: Mascoutah Elementary School | Statement: [Mascoutah, Illinois, hasPublicElementarySchool, Mascoutah 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: Mascoutah Elementary School
Triple: [Mascoutah, Illinois, hasPublicElementarySchool, Mascoutah Elementary School]
Generated description
Mascoutah Elementary School is a public primary school serving young students in the community of Mascoutah, Illinois.

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_69f224a5d2b481908a6853cd0138e2d7 completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69f68a9478808190918446246537dcdd completed May 2, 2026, 11:36 p.m.
NED1 Entity disambiguation (via context triple) batch_6a28b07d5f208190a6cb63e062cb6557 completed June 10, 2026, 12:31 a.m.
NEDg Description generation batch_6a28b1b3d41481908b42370b7ad16ba4 completed June 10, 2026, 12:37 a.m.
NED2 Entity disambiguation (via description) batch_6a28b2561d808190b5fbfc96e46634df completed June 10, 2026, 12:39 a.m.
Created at: April 29, 2026, 8:29 p.m.