Triple
T19731787
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maria Manuela Ramalho Eanes |
E473871
|
entity |
| Predicate | publicFigureType |
P116630
|
FINISHED |
| Object | political spouse |
—
|
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: political spouse | Statement: [Maria Manuela Ramalho Eanes, publicFigureType, political spouse]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: publicFigureType Context triple: [Maria Manuela Ramalho Eanes, publicFigureType, political spouse]
-
A.
publicFigure
Indicates that an entity is widely recognized by the public and holds a prominent or influential role in society, such as in politics, entertainment, or media.
-
B.
figureType
chosen
Indicates that one entity is classified as a specific type or category of figure in relation to another entity.
-
C.
typeOfFigure
Indicates that one entity is a specific kind or category of geometric figure relative to another.
-
D.
typicalFigure
Indicates that one entity serves as a standard or representative example (a typical instance) of the other entity.
-
E.
trainedFigure
Indicates that one entity has been trained, coached, or otherwise prepared by another entity.
- 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_69d8e517ebd48190979ee76723bcfadf |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e649fd18148190a6e85b2be0069dde |
completed | April 20, 2026, 3:45 p.m. |
| PD | Predicate disambiguation | batch_69e5304a7aac8190ac13f75f0c008e45 |
completed | April 19, 2026, 7:43 p.m. |
Created at: April 10, 2026, 1:47 p.m.