Triple
T12209068
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Iraqi diaspora |
E290908
|
entity |
| Predicate | hasReligiousComposition |
P103808
|
FINISHED |
| Object | Muslims |
—
|
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: Muslims | Statement: [Iraqi diaspora, hasReligiousComposition, Muslims]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasReligiousComposition Context triple: [Iraqi diaspora, hasReligiousComposition, Muslims]
-
A.
ethnicReligionMix
Indicates a relationship where a group or context involves a combined or overlapping presence of specific ethnic identities and religious affiliations.
-
B.
religiousCompositionHistorical
Indicates the historical distribution or makeup of religious affiliations within a population or group over time.
-
C.
hasEthnoReligiousDimension
Indicates that the relationship, event, or phenomenon involves or is characterized by an ethnic and/or religious aspect or component.
-
D.
hasPoliticalComposition
Indicates that an entity has a particular political makeup or distribution of political affiliations, parties, or ideologies.
-
E.
ethnicOrReligiousGroup
Indicates that one entity is an ethnic or religious group to which the other entity belongs or with which it is associated.
- 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_69d6ab65923081909acfc61b7a612233 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d920e312708190b4aede2e21f5f697 |
completed | April 10, 2026, 4:10 p.m. |
| PD | Predicate disambiguation | batch_69d91c3d669c81908eea7ad61122d275 |
completed | April 10, 2026, 3:50 p.m. |
| PDg | Predicate description generation | batch_69d920c3dc9881908c396a4ab34f4836 |
completed | April 10, 2026, 4:09 p.m. |
Created at: April 8, 2026, 9:51 p.m.