Triple

T28040872
Position Surface form Disambiguated ID Type / Status
Subject Midland City, Alabama E708534 entity
Predicate hasPublicSchoolSystem P226 FINISHED
Object Dale County Schools
Dale County Schools is the public school district serving students in Midland City and surrounding areas of Dale County, Alabama.
E1798867 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: Dale County Schools | Statement: [Midland City, Alabama, hasPublicSchoolSystem, Dale County Schools]
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: Dale County Schools
Triple: [Midland City, Alabama, hasPublicSchoolSystem, Dale County Schools]
Generated description
Dale County Schools is the public school district serving students in Midland City and surrounding areas of Dale County, Alabama.

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_69ef9b6cf538819094a633ffa67afec1 completed April 27, 2026, 5:22 p.m.
NER Named-entity recognition batch_69f63f2fb6548190b187123a2250cea6 completed May 2, 2026, 6:15 p.m.
NED1 Entity disambiguation (via context triple) batch_6a15b8b8ecf48190ad708d739dd9c464 completed May 26, 2026, 3:14 p.m.
NEDg Description generation batch_6a15b97876388190882b42942fc86c3c completed May 26, 2026, 3:17 p.m.
NED2 Entity disambiguation (via description) batch_6a15ba15ed6481908eadd24fa99efccf completed May 26, 2026, 3:19 p.m.
Created at: April 27, 2026, 8:25 p.m.