Triple

T34929449
Position Surface form Disambiguated ID Type / Status
Subject Northampton, Pennsylvania E1007388 entity
Predicate hasHighSchool P113 FINISHED
Object Northampton Area High School
Northampton Area High School is a public secondary school serving students in the Northampton Area School District in Northampton, Pennsylvania.
E2059531 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: Northampton Area High School | Statement: [Northampton, Pennsylvania, hasHighSchool, Northampton Area 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: Northampton Area High School
Triple: [Northampton, Pennsylvania, hasHighSchool, Northampton Area High School]
Generated description
Northampton Area High School is a public secondary school serving students in the Northampton Area School District in Northampton, 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_69f76dc3d83881909d5c3c14455cfa2c completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_69f7825428188190ae58bf39c925d478 completed May 3, 2026, 5:13 p.m.
NED1 Entity disambiguation (via context triple) batch_6a37b26447cc8190a75dcc83b3110ef5 completed June 21, 2026, 9:44 a.m.
NEDg Description generation batch_6a37b3c955c88190989d0c2404a72ed1 completed June 21, 2026, 9:50 a.m.
NED2 Entity disambiguation (via description) batch_6a37b51173808190a8314a275b7c87d7 completed June 21, 2026, 9:55 a.m.
Created at: May 3, 2026, 4 p.m.