Triple
T31152630
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dr. Farrokh Daruwalla |
E794118
|
entity |
| Predicate | hasComplexProfessionalLife |
P203710
|
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, hasComplexProfessionalLife, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasComplexProfessionalLife Context triple: [Dr. Farrokh Daruwalla, hasComplexProfessionalLife, yes]
-
A.
hasComplexPersonalLife
Indicates that an entity’s personal relationships, circumstances, or emotional life involve multiple intertwined factors, conflicts, or complications rather than being straightforward or simple.
-
B.
hasAdultLifeIn
Indicates that an entity spends or experiences its adult stage of life within a specified location or environment.
-
C.
hasProfessionalCareer
Indicates that an entity engages in or has engaged in a recognized professional occupation or career over a period of time.
-
D.
hasProfessionalSection
Indicates that an entity includes or is associated with a designated professional section, division, or category within its structure or content.
-
E.
hasDualCareer
Indicates that an entity simultaneously maintains two distinct professional roles or career paths.
- 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_6a01ccd995e48190b6675e463bd0a567 |
completed | May 11, 2026, 12:34 p.m. |
| PD | Predicate disambiguation | batch_6a01cc33177c8190bc0703276618b3ec |
completed | May 11, 2026, 12:31 p.m. |
| PDg | Predicate description generation | batch_6a01ccd8c6108190b4b0e991805a750d |
completed | May 11, 2026, 12:34 p.m. |
Created at: April 29, 2026, 9:06 p.m.