Triple
T36944263
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vidyavati Sharma |
E913861
|
entity |
| Predicate | spouseTermOverlapWith |
P197471
|
FINISHED |
| Object | Presidency of Shankar Dayal Sharma |
—
|
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: Presidency of Shankar Dayal Sharma | Statement: [Vidyavati Sharma, spouseTermOverlapWith, Presidency of Shankar Dayal Sharma]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: spouseTermOverlapWith Context triple: [Vidyavati Sharma, spouseTermOverlapWith, Presidency of Shankar Dayal Sharma]
-
A.
spouseTermCoincidesWith
Indicates that the term used to refer to a spouse coincides exactly with another specified term in form or usage.
-
B.
spouseWorkWith
Indicates that a person’s spouse works together with a specified person, typically as colleagues in the same workplace or professional context.
-
C.
hasCollaborativeRoleWithSpouse
Indicates that an individual shares a joint, cooperative role or responsibility together with their spouse.
-
D.
spouseMemberOf
Indicates that a person’s spouse is a member of a specified group, organization, or entity.
-
E.
spouseInstanceOf
Indicates that one entity is the specific spouse (marriage partner) instance of another entity.
- 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_69f76e8a6a5c81909c1febf32bf3fe23 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fe920a437081908d5174e8cf7a53a6 |
completed | May 9, 2026, 1:46 a.m. |
| PD | Predicate disambiguation | batch_69fe919a9a6c8190acb4483f386e6db7 |
completed | May 9, 2026, 1:44 a.m. |
| PDg | Predicate description generation | batch_69fe9208ed708190980fb5061b22ae49 |
completed | May 9, 2026, 1:46 a.m. |
Created at: May 3, 2026, 4:13 p.m.