Triple
T31152629
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dr. Farrokh Daruwalla |
E794118
|
entity |
| Predicate | hasComplexPersonalLife |
P203703
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Dr. Farrokh Daruwalla, hasComplexPersonalLife, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasComplexPersonalLife Context triple: [Dr. Farrokh Daruwalla, hasComplexPersonalLife, yes]
-
A.
hasPersonalLife
Indicates that an entity has aspects, activities, or relationships belonging to its private or non-professional life.
-
B.
hasAdultLifeIn
Indicates that an entity spends or experiences its adult stage of life within a specified location or environment.
-
C.
hasParallelLifeWith
Indicates that two entities lead or experience lives that run alongside each other in similar, corresponding, or contemporaneous ways without fully intersecting.
-
D.
hasPartInLife
Indicates that an entity participates in, contributes to, or plays a role within some aspect or period of another entity’s life.
-
E.
inPersonalLifeImplies
Indicates that a condition or fact in a person's private or non-professional life logically leads to, or has consequences for, another situation or fact.
- 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_69f224d41bb48190a5621cd1485e3a30 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_6a01cb89ff448190b60ee3d148ce76fc |
completed | May 11, 2026, 12:28 p.m. |
| PD | Predicate disambiguation | batch_6a01ca7604b48190bb8643c17c3a8c85 |
completed | May 11, 2026, 12:24 p.m. |
| PDg | Predicate description generation | batch_6a01cb8914048190a5e60e5639b1f88b |
completed | May 11, 2026, 12:28 p.m. |
Created at: April 29, 2026, 9:06 p.m.