Triple

T25660147
Position Surface form Disambiguated ID Type / Status
Subject Columbia Heights, Minnesota E643353 entity
Predicate publicElementarySchool P43431 FINISHED
Object Highland Elementary School
Highland Elementary School is a public primary school serving young students in the Columbia Heights community of Minnesota.
E1693464 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: Highland Elementary School | Statement: [Columbia Heights, Minnesota, publicElementarySchool, Highland 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: Highland Elementary School
Triple: [Columbia Heights, Minnesota, publicElementarySchool, Highland Elementary School]
Generated description
Highland Elementary School is a public primary school serving young students in the Columbia Heights community of Minnesota.

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_69e77e7e45648190a068ed3faa8016ea completed April 21, 2026, 1:41 p.m.
NER Named-entity recognition batch_69f5faee68408190b602dc71ec5b83aa completed May 2, 2026, 1:23 p.m.
NED1 Entity disambiguation (via context triple) batch_6a10cbeb09b08190aaec199ad6ae0835 completed May 22, 2026, 9:34 p.m.
NEDg Description generation batch_6a10ccedad64819080986fe4cae5a969 completed May 22, 2026, 9:38 p.m.
NED2 Entity disambiguation (via description) batch_6a10cdf9537481909131c59b126e69b6 completed May 22, 2026, 9:43 p.m.
Created at: April 21, 2026, 6:51 p.m.