Triple
T7688494
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Florida Department of Financial Services headquarters |
E174184
|
entity |
| Predicate | hasAgencyType |
P3504
|
FINISHED |
| Object | state executive agency headquarters |
—
|
LITERAL 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: state executive agency headquarters | Statement: [Florida Department of Financial Services headquarters, hasAgencyType, state executive agency headquarters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAgencyType Context triple: [Florida Department of Financial Services headquarters, hasAgencyType, state executive agency headquarters]
-
A.
hasKeyAgency
Indicates that an entity serves as the primary responsible or controlling agency for another entity, action, or process.
-
B.
hasAgencySupport
Indicates that an entity receives backing, assistance, or sponsorship from an agency.
-
C.
hasAgent
Indicates that an action or event is carried out or initiated by a particular agent.
-
D.
hasAffiliationType
Indicates that one entity is connected to another through a specified kind or category of affiliation or association.
-
E.
hasTypeOfOrganization
chosen
Indicates that an entity is classified as belonging to a particular type or category of organization.
- F. None of above.
Provenance (3 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_69c6995966348190939e6c37ba272c06 |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c706d1f0208190bc5b695aa5736244 |
completed | March 27, 2026, 10:38 p.m. |
| PD | Predicate disambiguation | batch_69c70163dea88190ae729df50e63dfd7 |
completed | March 27, 2026, 10:15 p.m. |
Created at: March 27, 2026, 4:02 p.m.