Triple
T467247
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Madam Secretary |
E8474
|
entity |
| Predicate | usedToAddress |
P6238
|
FINISHED |
| Object | female United States Secretary of State |
—
|
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: female United States Secretary of State | Statement: [Madam Secretary, usedToAddress, female United States Secretary of State]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedToAddress Context triple: [Madam Secretary, usedToAddress, female United States Secretary of State]
-
A.
hasAddress
Indicates that an entity is associated with a specific address or location.
-
B.
usedAt
Indicates that something is employed, applied, or utilized at a particular place, time, or context.
-
C.
designationUsedFor
chosen
Indicates that a particular name, label, or title is employed to refer to or identify a specific entity or role.
-
D.
usesAddressingSystem
Indicates that one entity employs or applies a particular addressing system associated with another entity.
-
E.
usedFor
Indicates that one entity serves a purpose, function, or role in accomplishing, enabling, or supporting another entity or activity.
- 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_69a2e7f3aeb48190a19453e3a043f486 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2efd831088190b6ac6a56b34a8816 |
completed | Feb. 28, 2026, 1:38 p.m. |
| PD | Predicate disambiguation | batch_69a2edebb3988190907992a584b4e260 |
completed | Feb. 28, 2026, 1:30 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.