Triple
T31294258
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Executive Office of Public Safety and Security |
E798032
|
entity |
| Predicate | hasCabinetStatus |
P196983
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Executive Office of Public Safety and Security, hasCabinetStatus, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCabinetStatus Context triple: [Executive Office of Public Safety and Security, hasCabinetStatus, true]
-
A.
hasCabinet
Indicates that one entity possesses, includes, or is equipped with a cabinet associated with it.
-
B.
isInCabinet
Indicates that one entity serves as a member of the governing cabinet associated with another entity (such as a government or administration).
-
C.
hasCabinetName
Indicates that an entity is associated with a specific cabinet by its name.
-
D.
hasCabinetRole
Indicates that an entity holds or is assigned a specific role or position within a cabinet (such as a governmental or executive cabinet).
-
E.
chamberStatus
Indicates the current operational or physical condition of a chamber within a system or process.
- F. None of above. chosen
Provenance (4 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_69f224dfde288190af313f3c221c857e |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69fe72dca2f08190beff17de3d2aada6 |
completed | May 8, 2026, 11:33 p.m. |
| PD | Predicate disambiguation | batch_69fe70bca8d08190b810e1e616ceac44 |
completed | May 8, 2026, 11:24 p.m. |
| PDg | Predicate description generation | batch_69fe72db8810819089e397961b8ead7a |
completed | May 8, 2026, 11:33 p.m. |
Created at: April 29, 2026, 9:14 p.m.