Triple
T35086740
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Barbara Schellekens |
E1012597
|
entity |
| Predicate | marriedToCartographer |
P194823
|
FINISHED |
| Object | Gerardus Mercator |
—
|
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: Gerardus Mercator | Statement: [Barbara Schellekens, marriedToCartographer, Gerardus Mercator]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: marriedToCartographer Context triple: [Barbara Schellekens, marriedToCartographer, Gerardus Mercator]
-
A.
marriedToExplorer
Indicates that one entity is legally married to another entity who is an explorer.
-
B.
marriedToPainter
Indicates that one entity is married to another entity who is a painter.
-
C.
marriedToPhotographer
Indicates that one person is legally married to another person whose profession or primary role is that of a photographer.
-
D.
marriedBy
Indicates that one entity is the officiant or authority who performs and formalizes the marriage of another entity.
-
E.
marriedToPoet
Indicates that one person is married to another person who is a poet.
- 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_69f76dd32c008190853aef6028f60208 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69fd884cb2b48190b6acd473430d9e19 |
completed | May 8, 2026, 6:53 a.m. |
| PD | Predicate disambiguation | batch_69fd8709ca208190a8bab836f0156af5 |
completed | May 8, 2026, 6:47 a.m. |
| PDg | Predicate description generation | batch_69fd884b9d908190833de9500ff6d62a |
completed | May 8, 2026, 6:52 a.m. |
Created at: May 3, 2026, 4:01 p.m.