Triple

T29868495
Position Surface form Disambiguated ID Type / Status
Subject Bushnell, Florida E758520 entity
Predicate isServedByHighway P385 FINISHED
Object Florida State Road 475
Florida State Road 475 is a north–south state highway in central Florida that serves as an alternate route to U.S. Route 301, passing through areas including Bushnell.
E1904095 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: Florida State Road 475 | Statement: [Bushnell, Florida, isServedByHighway, Florida State Road 475]
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: Florida State Road 475
Triple: [Bushnell, Florida, isServedByHighway, Florida State Road 475]
Generated description
Florida State Road 475 is a north–south state highway in central Florida that serves as an alternate route to U.S. Route 301, passing through areas including Bushnell.

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_69f2245d0d7081909e37ee328542bcd7 completed April 29, 2026, 3:31 p.m.
NER Named-entity recognition batch_69f6768b2bf48190af4821d43d7ee766 completed May 2, 2026, 10:11 p.m.
NED1 Entity disambiguation (via context triple) batch_6a2757f2c30481908459c219ca49c52b completed June 9, 2026, 12:01 a.m.
NEDg Description generation batch_6a275a7d33848190ba11aeb45c7e8b83 completed June 9, 2026, 12:12 a.m.
NED2 Entity disambiguation (via description) batch_6a275b11987081908ec648ce1eeceed3 completed June 9, 2026, 12:15 a.m.
Created at: April 29, 2026, 5:52 p.m.