Triple

T36950664
Position Surface form Disambiguated ID Type / Status
Subject Jordy Nelson E914052 entity
Predicate highSchoolAttended P5 FINISHED
Object Riley County High School
Riley County High School is a public secondary school in Riley, Kansas, best known for being the alma mater of former NFL wide receiver Jordy Nelson.
E2206065 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: Riley County High School | Statement: [Jordy Nelson, highSchoolAttended, Riley County 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: Riley County High School
Triple: [Jordy Nelson, highSchoolAttended, Riley County High School]
Generated description
Riley County High School is a public secondary school in Riley, Kansas, best known for being the alma mater of former NFL wide receiver Jordy Nelson.

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_69f76e8b28848190abd81fe7a7374910 completed May 3, 2026, 3:49 p.m.
NER Named-entity recognition batch_69f9fedbbbd8819085e8be4af270ac16 completed May 5, 2026, 2:29 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3e2c3648d48190bab863d38dd6abf7 completed June 26, 2026, 7:37 a.m.
NEDg Description generation batch_6a3e2d0b7b9081908b0a1754dfbea0df completed June 26, 2026, 7:40 a.m.
NED2 Entity disambiguation (via description) batch_6a3e40f1c27c8190aacf64bbd31eb44b completed June 26, 2026, 9:05 a.m.
Created at: May 3, 2026, 4:13 p.m.