Triple
T24479659
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Duchess of Mortemart |
E617334
|
entity |
| Predicate | courtRoleContext |
P45619
|
FINISHED |
| Object | Versailles court society |
—
|
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: Versailles court society | Statement: [Duchess of Mortemart, courtRoleContext, Versailles court society]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: courtRoleContext Context triple: [Duchess of Mortemart, courtRoleContext, Versailles court society]
-
A.
courtRole
Indicates the specific capacity or position an entity holds within a court proceeding or judicial context.
-
B.
roleAtCourt
chosen
Indicates the specific position, function, or status an entity holds within a court or courtly setting.
-
C.
judicialRole
Indicates that one entity holds or performs a specific official function or position within the judicial system in relation to another entity or legal matter.
-
D.
courtContext
Indicates the legal or judicial setting, circumstances, or framework within which a court-related action or relationship takes place.
-
E.
legalCaseRole
Indicates the specific role or capacity an entity holds within a legal case, such as plaintiff, defendant, judge, or attorney.
- 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_69e2d7f3ae788190b683394db15f220e |
completed | April 18, 2026, 1:01 a.m. |
| NER | Named-entity recognition | batch_69f29ed509c88190a0071f8e78b38887 |
completed | April 30, 2026, 12:14 a.m. |
| PD | Predicate disambiguation | batch_69f287d76c7c81909494f12e606a9149 |
completed | April 29, 2026, 10:36 p.m. |
Created at: April 18, 2026, 2:21 a.m.