Triple

T27027757
Position Surface form Disambiguated ID Type / Status
Subject Florida General Revenue Fund E680834 entity
Predicate relatedTo P37 FINISHED
Object Florida trust funds
Florida trust funds are specialized state financial accounts in Florida used to collect and allocate revenues for specific purposes such as education, transportation, and environmental programs, separate from the state’s general revenue.
E1755640 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 trust funds | Statement: [Florida General Revenue Fund, relatedTo, Florida trust funds]
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 trust funds
Triple: [Florida General Revenue Fund, relatedTo, Florida trust funds]
Generated description
Florida trust funds are specialized state financial accounts in Florida used to collect and allocate revenues for specific purposes such as education, transportation, and environmental programs, separate from the state’s general revenue.

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_69eeeb5566f08190813daf896fa3da04 completed April 27, 2026, 4:51 a.m.
NER Named-entity recognition batch_69f62232f1048190be9e9467cd181055 completed May 2, 2026, 4:11 p.m.
NED1 Entity disambiguation (via context triple) batch_6a123aba8fd08190a1ad9fc2d57685d7 completed May 23, 2026, 11:39 p.m.
NEDg Description generation batch_6a123bbe49cc81908763b340636d7a60 completed May 23, 2026, 11:43 p.m.
NED2 Entity disambiguation (via description) batch_6a123f9c03f881908e9cc1bc292b3e96 completed May 24, 2026, midnight
Created at: April 27, 2026, 7:12 a.m.