Triple
T22914393
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kavita Krishnamurti |
E568688
|
entity |
| Predicate | hasStepChildren |
P25182
|
FINISHED |
| Object | 4 |
—
|
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: 4 | Statement: [Kavita Krishnamurti, hasStepChildren, 4]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasStepChildren Context triple: [Kavita Krishnamurti, hasStepChildren, 4]
-
A.
hasStepchildren
chosen
Indicates that one person has stepchildren, meaning children of their spouse or partner from a previous relationship.
-
B.
hasStepSibling
Indicates that one person is the step-sibling of another, meaning they are related through the marriage of their parents rather than by blood or adoption.
-
C.
hasStep
Indicates that one entity includes, is composed of, or is associated with a specific step or stage in a process involving another entity.
-
D.
hasStepFamily
Indicates that one person is related to another as a member of a stepfamily, such as a stepparent, stepchild, or stepsibling, through marriage rather than blood or adoption.
-
E.
hasStepsLeadingTo
Indicates that one location or object is connected to another by a set of steps or a staircase leading toward it.
- 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_69e2458d90c88190a58cead4e781ca6a |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f18078077881908b8124cc22110c6e |
completed | April 29, 2026, 3:52 a.m. |
| PD | Predicate disambiguation | batch_69ef3b7c5fc081909ac50c5c8569cc19 |
completed | April 27, 2026, 10:33 a.m. |
Created at: April 17, 2026, 3:42 p.m.