Triple

T23849778
Position Surface form Disambiguated ID Type / Status
Subject Ashtabula, Ohio E592126 entity
Predicate hasEducationalInstitution P113 FINISHED
Object Ashtabula Area City School District
Ashtabula Area City School District is a public school district that serves students in the Ashtabula, Ohio area.
E1606147 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: Ashtabula Area City School District | Statement: [Ashtabula, Ohio, hasEducationalInstitution, Ashtabula Area City 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: Ashtabula Area City School District
Triple: [Ashtabula, Ohio, hasEducationalInstitution, Ashtabula Area City School District]
Generated description
Ashtabula Area City School District is a public school district that serves students in the Ashtabula, Ohio area.

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_69e25d221d908190b9b502ad31e66a3f completed April 17, 2026, 4:17 p.m.
NER Named-entity recognition batch_69f1c986f7e08190a6d361423946ff05 completed April 29, 2026, 9:04 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0f69aeca648190aafbf47046e0bc32 completed May 21, 2026, 8:23 p.m.
NEDg Description generation batch_6a0f6d4205ac8190a2be21159c3117bf completed May 21, 2026, 8:38 p.m.
NED2 Entity disambiguation (via description) batch_6a0f6e5bceb88190ae077c6b68bc25c1 completed May 21, 2026, 8:43 p.m.
Created at: April 17, 2026, 8:11 p.m.