Triple
T33133438
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Florence Caroline Lascelles |
E847935
|
entity |
| Predicate | marriedToDiplomat |
P125296
|
FINISHED |
| Object | Cecil Spring Rice |
—
|
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: Cecil Spring Rice | Statement: [Florence Caroline Lascelles, marriedToDiplomat, Cecil Spring Rice]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: marriedToDiplomat Context triple: [Florence Caroline Lascelles, marriedToDiplomat, Cecil Spring Rice]
-
A.
spouseDiplomaticRole
chosen
Indicates that one person is the spouse of another person who holds or held a diplomatic position or role.
-
B.
marriedToHeadOfGovernmentOf
Indicates that one entity is the spouse of the person who holds the position of head of government of the other entity.
-
C.
marriedToPolitician
Indicates that a person is married to someone who holds or has held a political office or role.
-
D.
marriedBy
Indicates that one entity is the officiant or authority who performs and formalizes the marriage of another entity.
-
E.
marriedToDuringOffice
Indicates that one person was married to another person specifically during the time they held a particular office or position.
- 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_69f3495961d88190b16ea542c2c5f825 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69fd231cab588190ad0953dc8f4af8f2 |
completed | May 7, 2026, 11:41 p.m. |
| PD | Predicate disambiguation | batch_69fd1aa3f1c481909fe6e9cab1383551 |
completed | May 7, 2026, 11:05 p.m. |
Created at: May 1, 2026, 1:27 a.m.