Triple

T31890884
Position Surface form Disambiguated ID Type / Status
Subject Elizabethtown Area School District E814141 entity
Predicate hasElementarySchool P113 FINISHED
Object Rheems Elementary School
Rheems Elementary School is a public elementary school serving early-grade students in the Elizabethtown Area region of Pennsylvania.
E1982871 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: Rheems Elementary School | Statement: [Elizabethtown Area School District, hasElementarySchool, Rheems 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: Rheems Elementary School
Triple: [Elizabethtown Area School District, hasElementarySchool, Rheems Elementary School]
Generated description
Rheems Elementary School is a public elementary school serving early-grade students in the Elizabethtown Area region of Pennsylvania.

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_69f348ef817481908440e2250319bcc8 completed April 30, 2026, 12:19 p.m.
NER Named-entity recognition batch_69f6b158cc5c81909ce5b32c9a97ae72 completed May 3, 2026, 2:22 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2e7fea67308190836c472585529018 completed June 14, 2026, 10:18 a.m.
NEDg Description generation batch_6a2e8147b47c81908330d72c3691c514 completed June 14, 2026, 10:24 a.m.
NED2 Entity disambiguation (via description) batch_6a2e820f7e888190b36e8bef42a391c7 completed June 14, 2026, 10:27 a.m.
Created at: April 30, 2026, 11:58 p.m.