Triple
T25942955
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Princess Henry of Battenberg |
E653755
|
entity |
| Predicate | followsMarriageTo |
P168044
|
FINISHED |
| Object | Prince Henry of Battenberg |
—
|
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: Prince Henry of Battenberg | Statement: [Princess Henry of Battenberg, followsMarriageTo, Prince Henry of Battenberg]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: followsMarriageTo Context triple: [Princess Henry of Battenberg, followsMarriageTo, Prince Henry of Battenberg]
-
A.
resultedInMarriageTo
Indicates that one event, action, or circumstance led to or caused a marriage to occur between the related entities.
-
B.
marriedBy
Indicates that one entity is the officiant or authority who performs and formalizes the marriage of another entity.
-
C.
marriesFor
Indicates that one entity enters into marriage with another entity specifically for a particular reason, motive, or benefit.
-
D.
marries
Indicates that one entity enters into a legally or socially recognized marital union with another entity.
-
E.
hasMarriage
Indicates a marital relationship exists between the two entities, specifying that they are or were legally married to each other.
- 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_69e7ab3fd2f881908837305e4ba98011 |
completed | April 21, 2026, 4:52 p.m. |
| NER | Named-entity recognition | batch_69f673633d288190b52ceb9f8a057c44 |
completed | May 2, 2026, 9:57 p.m. |
| PD | Predicate disambiguation | batch_69f66ec3d3d48190ab2f2b71939e572e |
completed | May 2, 2026, 9:38 p.m. |
| PDg | Predicate description generation | batch_69f67256d064819094be04fc1bbbc635 |
completed | May 2, 2026, 9:53 p.m. |
Created at: April 22, 2026, 8:41 a.m.