Triple
T26715651
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Anna Brewster |
E673547
|
entity |
| Predicate | hasNotableRoleAs |
P27764
|
FINISHED |
| Object | Madame de Montespan in Versailles |
—
|
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: Madame de Montespan in Versailles | Statement: [Anna Brewster, hasNotableRoleAs, Madame de Montespan in Versailles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNotableRoleAs Context triple: [Anna Brewster, hasNotableRoleAs, Madame de Montespan in Versailles]
-
A.
hasNotableRoleIn
chosen
Indicates that an entity holds a significant or noteworthy role or function within another entity, event, work, or context.
-
B.
hasNotablePosition
Indicates that an entity holds or has held a position, role, or office considered notable or significant.
-
C.
mayHaveRole
Indicates that an entity is permitted or eligible to hold or perform a specified role.
-
D.
hasPlayingRole
Indicates that an entity participates in an activity, event, or performance in a specific playing role or capacity.
-
E.
hasRole
Indicates that an entity occupies, performs, or is assigned a specific role or function in relation to another entity or context.
- 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_69eecda3a22881908f3061c760b9d542 |
completed | April 27, 2026, 2:44 a.m. |
| NER | Named-entity recognition | batch_69fddac4e2f48190a9301d3422658b29 |
completed | May 8, 2026, 12:44 p.m. |
| PD | Predicate disambiguation | batch_69fdda06969c8190b5d033964ea2a690 |
completed | May 8, 2026, 12:41 p.m. |
Created at: April 27, 2026, 3:37 a.m.