Triple
T990681
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dudley |
E21380
|
entity |
| Predicate | semanticClass |
P7975
|
FINISHED |
| Object | anthroponym |
—
|
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: anthroponym | Statement: [Dudley, semanticClass, anthroponym]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: semanticClass Context triple: [Dudley, semanticClass, anthroponym]
-
A.
semanticType
chosen
Indicates that something belongs to or is categorized under a particular semantic class or type based on its meaning.
-
B.
semanticRelation
Indicates a general meaning-based connection between two entities, such as similarity, implication, or conceptual association.
-
C.
classificationStart
Indicates the point in time or process at which a classification or categorization of an entity begins.
-
D.
classificationSystem
Indicates a relationship where an entity is organized or categorized according to a particular classification scheme or taxonomy.
-
E.
subclassOf
Indicates that one class is a more specific type of another class, inheriting its characteristics as a subset of it.
- 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_69a493c383dc8190a03257f22d4b4183 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b4ac27e081908f132115464667b2 |
completed | March 1, 2026, 9:50 p.m. |
| PD | Predicate disambiguation | batch_69a4b2adbde48190b07966d0c3179516 |
completed | March 1, 2026, 9:42 p.m. |
Created at: March 1, 2026, 7:41 p.m.