Triple
T32135163
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Christian Iranians |
E820747
|
entity |
| Predicate | professionDistribution |
P174132
|
FINISHED |
| Object | significant participation in trade and commerce |
—
|
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: significant participation in trade and commerce | Statement: [Christian Iranians, professionDistribution, significant participation in trade and commerce]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: professionDistribution Context triple: [Christian Iranians, professionDistribution, significant participation in trade and commerce]
-
A.
occupationType
Indicates the specific kind or category of work, profession, or role that an entity performs or holds.
-
B.
professionalCategory
Indicates the classification of an entity according to its professional field, role, or occupational domain.
-
C.
professionalSector
Indicates the industry or field in which an entity conducts its professional or occupational activities.
-
D.
occupationSetting
Indicates the typical environment or context in which an occupation is performed.
-
E.
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.
- 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_69f349039e0c819091c7a7d322e3f46d |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6bcc425588190afd0dceba43ed79f |
completed | May 3, 2026, 3:11 a.m. |
| PD | Predicate disambiguation | batch_69f6ba6cef208190bc5cd43d96127004 |
completed | May 3, 2026, 3:01 a.m. |
| PDg | Predicate description generation | batch_69f6bbbe23d48190b2aa662d69b41900 |
completed | May 3, 2026, 3:06 a.m. |
Created at: May 1, 2026, 12:30 a.m.