Triple

T35247116
Position Surface form Disambiguated ID Type / Status
Subject Homer Hoyt E1017697 entity
Predicate hasConceptNamedAfter P3325 FINISHED
Object Hoyt model of urban land use
The Hoyt model of urban land use is a sector-based theory of city structure that explains how different types of land use develop in wedge-shaped sectors radiating out from the city center, largely influenced by transportation routes.
E2130479 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: Hoyt model of urban land use | Statement: [Homer Hoyt, hasConceptNamedAfter, Hoyt model of urban land use]
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: Hoyt model of urban land use
Triple: [Homer Hoyt, hasConceptNamedAfter, Hoyt model of urban land use]
Generated description
The Hoyt model of urban land use is a sector-based theory of city structure that explains how different types of land use develop in wedge-shaped sectors radiating out from the city center, largely influenced by transportation routes.

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_69f76de235048190b990070c23c51b6b completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_69f78f32948c81909b7c4a5f3f119147 completed May 3, 2026, 6:08 p.m.
NED1 Entity disambiguation (via context triple) batch_6a38042775dc819093cacb0c7a291e5d completed June 21, 2026, 3:32 p.m.
NEDg Description generation batch_6a380492146c819091e84a4db90e432f completed June 21, 2026, 3:34 p.m.
NED2 Entity disambiguation (via description) batch_6a38054099408190b0a218ecb7f84dc6 completed June 21, 2026, 3:37 p.m.
Created at: May 3, 2026, 4:02 p.m.