Triple
T2587129
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Catherine of Braganza |
E58030
|
entity |
| Predicate | roleInPortugal |
P40542
|
FINISHED |
| Object | regent of Portugal |
—
|
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: regent of Portugal | Statement: [Catherine of Braganza, roleInPortugal, regent of Portugal]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roleInPortugal Context triple: [Catherine of Braganza, roleInPortugal, regent of Portugal]
-
A.
roleInEurope
Indicates that an entity holds a specific function, position, or responsibility within a European context, such as within Europe as a region or its institutions.
-
B.
roleInCanada
Indicates that one entity holds or performs a specific role, position, or function within the context of Canada.
-
C.
ethnicRole
Indicates a role, function, or social position that is specifically associated with or defined by an entity’s ethnicity.
-
D.
roleInText
Indicates that an entity participates in a text with a specific function or capacity (e.g., author, editor, character).
-
E.
roleInTSEliotLife
Indicates the specific role, involvement, or significance an entity had in T. S. Eliot’s life.
- F. None of above. chosen
Provenance (4 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_69ab4ac019c8819094add11c46706e32 |
completed | March 6, 2026, 9:44 p.m. |
| NER | Named-entity recognition | batch_69abd3f8a3888190889c537e6df07305 |
completed | March 7, 2026, 7:30 a.m. |
| PD | Predicate disambiguation | batch_69abd0d19308819089ee942513d567a4 |
completed | March 7, 2026, 7:16 a.m. |
| PDg | Predicate description generation | batch_69abd37ef248819090ab6b86b67e355f |
completed | March 7, 2026, 7:27 a.m. |
Created at: March 6, 2026, 9:49 p.m.