Triple
T14268443
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hassan Ali Khaire |
E353711
|
entity |
| Predicate | sectorWorkedIn |
P62124
|
FINISHED |
| Object | non-governmental organizations |
—
|
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: non-governmental organizations | Statement: [Hassan Ali Khaire, sectorWorkedIn, non-governmental organizations]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sectorWorkedIn Context triple: [Hassan Ali Khaire, sectorWorkedIn, non-governmental organizations]
-
A.
occupationType
Indicates the specific kind or category of work, profession, or role that an entity performs or holds.
-
B.
employmentBasedCategory
Indicates that one entity’s classification or status is determined by its relationship to employment, such as being based on a specific job, role, or work-related category.
-
C.
careerField
Indicates the professional domain or occupational area in which an entity works or specializes.
-
D.
professionalSector
chosen
Indicates the industry or field in which an entity conducts its professional or occupational activities.
-
E.
workedPrimarilyOn
Indicates that an entity devoted the majority of its work, effort, or activity to a particular project, field, or subject.
- 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_69d8278d25148190abf1a8c8f5f533ad |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de6358c2288190ac1fd26e688a605d |
completed | April 14, 2026, 3:55 p.m. |
| PD | Predicate disambiguation | batch_69de2a7d586c8190846ff242bbf5ac53 |
completed | April 14, 2026, 11:52 a.m. |
Created at: April 10, 2026, 1:10 a.m.