Triple
T14085962
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Children’s Poet |
E338996
|
entity |
| Predicate | personHasNotableStyle |
P112750
|
FINISHED |
| Object | Hoosier dialect |
—
|
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: Hoosier dialect | Statement: [Children’s Poet, personHasNotableStyle, Hoosier dialect]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: personHasNotableStyle Context triple: [Children’s Poet, personHasNotableStyle, Hoosier dialect]
-
A.
fashionStyle
Indicates the characteristic way in which an entity dresses or presents themselves in terms of clothing and appearance.
-
B.
fashionCharacteristic
Indicates a relationship where one entity possesses or exhibits a particular style, trend, or fashion-related attribute in relation to another.
-
C.
styledCelebrity
Indicates that one entity (typically a stylist or source) is responsible for selecting or creating the fashion or appearance of a celebrity.
-
D.
styleTendsTo
Indicates that one style is generally inclined or likely to develop, appear, or be adopted in the direction of another style.
-
E.
styleCategory
Indicates the stylistic classification or genre category that an item, work, or entity belongs to.
- 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_69d81c687b0c819087fd9ed4198403f8 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de5edff1b881909ea56dc2429ef2dd |
completed | April 14, 2026, 3:36 p.m. |
| PD | Predicate disambiguation | batch_69de05b0e6c88190a819eeba0028981f |
completed | April 14, 2026, 9:15 a.m. |
| PDg | Predicate description generation | batch_69de2398856c81908bed6070e4ca6ab1 |
completed | April 14, 2026, 11:23 a.m. |
Created at: April 9, 2026, 10:21 p.m.