Triple
T10069451
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sophia Hull |
E213581
|
entity |
| Predicate | marriedToRole |
P37264
|
FINISHED |
| Object | Lieutenant-Governor of Java |
—
|
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: Lieutenant-Governor of Java | Statement: [Sophia Hull, marriedToRole, Lieutenant-Governor of Java]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: marriedToRole Context triple: [Sophia Hull, marriedToRole, Lieutenant-Governor of Java]
-
A.
marriedBy
Indicates that one entity is the officiant or authority who performs and formalizes the marriage of another entity.
-
B.
marriedToRank
chosen
Indicates that one entity is married to another entity who holds a specific rank or position.
-
C.
marriedInto
Indicates that one entity became connected to another’s family or group through marriage, rather than by birth or prior membership.
-
D.
hasCollaborativeRoleWithSpouse
Indicates that an individual shares a joint, cooperative role or responsibility together with their spouse.
-
E.
marriedIn
Indicates that two entities entered into a marital relationship at a specific place or within a particular jurisdiction.
- 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_69ca839add308190b57d53b4ec21f2d0 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cdcff8d9c08190bc030f1dcc696310 |
completed | April 2, 2026, 2:10 a.m. |
| PD | Predicate disambiguation | batch_69cd4b92573481909389bc6148ae7ea8 |
completed | April 1, 2026, 4:45 p.m. |
Created at: March 30, 2026, 8:58 p.m.