Triple

T25091645
Position Surface form Disambiguated ID Type / Status
Subject Prosper Town Hall E628476 entity
Predicate operator P179 FINISHED
Object Town of Prosper
The Town of Prosper is a rapidly growing suburban municipality in North Texas known for its family-oriented community, quality schools, and upscale residential developments.
 E1663187 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: Town of Prosper | Statement: [Prosper Town Hall, operator, Town of Prosper]
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: Town of Prosper
Triple: [Prosper Town Hall, operator, Town of Prosper]
Generated description
The Town of Prosper is a rapidly growing suburban municipality in North Texas known for its family-oriented community, quality schools, and upscale residential developments.

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_69e2ff2f58e881908340527bc5d34f07 completed April 18, 2026, 3:49 a.m.
NER Named-entity recognition batch_69f461eabb7c81909cfa0d5db8daca43 completed May 1, 2026, 8:18 a.m.
NED1 Entity disambiguation (via context triple) batch_6a1048e7b34c819091b5fcee22b145c0 completed May 22, 2026, 12:15 p.m.
NEDg Description generation batch_6a104a6df4208190b8fa9647b516b7fc completed May 22, 2026, 12:22 p.m.
NED2 Entity disambiguation (via description) batch_6a104c2d8308819097b21b979944585e completed May 22, 2026, 12:29 p.m.
Created at: April 18, 2026, 6:24 a.m.