Triple
T38687401
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Her Grace The Duchess of Norfolk |
E949155
|
entity |
| Predicate | formalPrecedenceStyle |
P102955
|
FINISHED |
| Object | The Most Noble |
—
|
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: The Most Noble | Statement: [Her Grace The Duchess of Norfolk, formalPrecedenceStyle, The Most Noble]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: formalPrecedenceStyle Context triple: [Her Grace The Duchess of Norfolk, formalPrecedenceStyle, The Most Noble]
-
A.
traditionalPrecedence
Indicates that one entity is accorded higher status, priority, or rank over another according to established tradition or customary order.
-
B.
ceremonialPrecedenceWithin
chosen
Indicates that one entity holds a higher or lower rank or priority than another within a specific ceremonial order or context.
-
C.
confersPrecedenceIn
Indicates that one entity is granted higher priority, rank, or standing over another within a specified context or domain.
-
D.
followsFormalTradition
Indicates that one entity adheres to or complies with an established formal tradition, convention, or set of customary practices associated with another entity.
-
E.
formalismType
Indicates the specific formal system or representational framework in which something (such as a theory, model, or specification) is expressed.
- 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_69f76efe16148190befd5dd59c3dfeaa |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fcef654d588190b29ecc76678d1aa0 |
completed | May 7, 2026, 8 p.m. |
| PD | Predicate disambiguation | batch_69fcecdb97f48190b382b7d13be92dc0 |
completed | May 7, 2026, 7:49 p.m. |
Created at: May 3, 2026, 4:33 p.m.