Triple

T36752698
Position Surface form Disambiguated ID Type / Status
Subject Village of Lyons E907955 entity
Predicate hasSchoolDistrict P226 FINISHED
Object Lyons Central School District
Lyons Central School District is a public school district serving students in and around the Village of Lyons in New York State.
E2196738 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: Lyons Central School District | Statement: [Village of Lyons, hasSchoolDistrict, Lyons Central School District]
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: Lyons Central School District
Triple: [Village of Lyons, hasSchoolDistrict, Lyons Central School District]
Generated description
Lyons Central School District is a public school district serving students in and around the Village of Lyons in New York State.

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_69f76e779bec8190be0e1f87a131e0f4 completed May 3, 2026, 3:49 p.m.
NER Named-entity recognition batch_69f7c944bbd081909ff6b83c36c70c37 completed May 3, 2026, 10:16 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3c17393e2881909965286d6943b26a completed June 24, 2026, 5:43 p.m.
NEDg Description generation batch_6a3c18c68ab48190aec3dcdb0a18931c completed June 24, 2026, 5:49 p.m.
NED2 Entity disambiguation (via description) batch_6a3c511a39308190ae3ba260b211948d completed June 24, 2026, 9:50 p.m.
Created at: May 3, 2026, 4:12 p.m.