Triple
T25508394
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Book VI |
E639305
|
entity |
| Predicate | dedicatedContext |
P114211
|
FINISHED |
| Object | court of Elizabeth I |
—
|
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: court of Elizabeth I | Statement: [Book VI, dedicatedContext, court of Elizabeth I]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: dedicatedContext Context triple: [Book VI, dedicatedContext, court of Elizabeth I]
-
A.
dedicated
Indicates that one entity is formally assigned, reserved, or committed for the specific use, benefit, or purpose of another entity.
-
B.
singleContext
Indicates that the entity or event occurs, is interpreted, or is valid within exactly one specific context, rather than across multiple contexts.
-
C.
primaryWorkContext
Indicates the main environment, setting, or domain in which an entity typically performs its work or primary activities.
-
D.
contextType
Indicates the type or category of contextual information associated with an entity or event.
-
E.
contextName
chosen
Indicates the specific contextual label or identifier under which an entity, event, or relation is defined or interpreted.
- 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_69e75dbd09308190b6b5f0afdc12ec6d |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f5f80749f88190a5c2a70e7370003b |
completed | May 2, 2026, 1:11 p.m. |
| PD | Predicate disambiguation | batch_69f468421ba08190880eac99135e5970 |
completed | May 1, 2026, 8:45 a.m. |
Created at: April 21, 2026, 2:48 p.m.