Triple
T34704590
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | First Lady of Kansas |
E1000466
|
entity |
| Predicate | customarilyStylesAs |
P37510
|
FINISHED |
| Object | First Lady |
—
|
NE NERFINISHED |
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: First Lady | Statement: [First Lady of Kansas, customarilyStylesAs, First Lady]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: customarilyStylesAs Context triple: [First Lady of Kansas, customarilyStylesAs, First Lady]
-
A.
styledAs
chosen
Indicates that one entity is presented, formatted, or designed in the manner, appearance, or aesthetic of another entity.
-
B.
usedStyle
Indicates that one entity employed or applied a particular style, method, or manner associated with another entity.
-
C.
usesAsStyleOf
Indicates that one entity adopts or applies another entity as a stylistic model, method, or manner of expression.
-
D.
styleTendsTo
Indicates that one style is generally inclined or likely to develop, appear, or be adopted in the direction of another style.
-
E.
passingStyle
Indicates the manner or technique by which something (typically a ball or object) is passed from one entity to another.
- 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_69f76dab937881909c86f1b9ad50445f |
completed | May 3, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_69f7805ce6208190ac6dbd9c97989978 |
completed | May 3, 2026, 5:05 p.m. |
| PD | Predicate disambiguation | batch_69f77956ec648190ba4fb7e9d83fd107 |
completed | May 3, 2026, 4:35 p.m. |
Created at: May 3, 2026, 3:59 p.m.