Triple
T23905224
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Royal Architect of Spain |
E601172
|
entity |
| Predicate | typicalWorkContext |
P48472
|
FINISHED |
| Object | courtly environment |
—
|
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: courtly environment | Statement: [Royal Architect of Spain, typicalWorkContext, courtly environment]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalWorkContext Context triple: [Royal Architect of Spain, typicalWorkContext, courtly environment]
-
A.
primaryWorkContext
chosen
Indicates the main environment, setting, or domain in which an entity typically performs its work or primary activities.
-
B.
employmentContext
Indicates the situational or organizational setting in which an employment relationship or work activity takes place.
-
C.
laborContext
Indicates the labor-related circumstances, conditions, or setting within which an action, relationship, or event takes place.
-
D.
workWithin
Indicates that one entity performs its activities or duties inside the boundaries, scope, or context defined by another entity.
-
E.
nationalContextOfWork
Indicates the country or national setting within which the work or activity is carried out.
- 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_69e295364a488190bcac702e9bb7f764 |
completed | April 17, 2026, 8:16 p.m. |
| NER | Named-entity recognition | batch_69f1cde13e88819086bbd0bc4a5b6a36 |
completed | April 29, 2026, 9:22 a.m. |
| PD | Predicate disambiguation | batch_69f1614e24b48190a1c8fb5b7c75ee0f |
completed | April 29, 2026, 1:39 a.m. |
Created at: April 17, 2026, 8:30 p.m.