Triple
T26139462
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mumbra |
E659474
|
entity |
| Predicate | religiousMinorityConcentrationArea |
P158963
|
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: [Mumbra, religiousMinorityConcentrationArea, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: religiousMinorityConcentrationArea Context triple: [Mumbra, religiousMinorityConcentrationArea, yes]
-
A.
religionSignificantMinorityRegion
Indicates that a particular religion constitutes a significant minority presence within a specified geographic region.
-
B.
religiousMinorityCommunity
Indicates a community whose members follow a religion that is numerically or socially less dominant within a larger societal or national context.
-
C.
religiousMinorityCenterFor
Indicates that a place or institution serves as a central hub or focal point for a specific religious minority group.
-
D.
minorityLocation
chosen
Indicates that a minority group is present, situated, or concentrated in a particular location or area.
-
E.
shareReligiousDemographics
Indicates that two entities have similar or identical distributions of religious affiliations within their populations.
- 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_69ee5bc3c20c8190bf2cf272f4170e95 |
completed | April 26, 2026, 6:38 p.m. |
| NER | Named-entity recognition | batch_69f7221dc9a88190bb8194fcc29c42bc |
completed | May 3, 2026, 10:23 a.m. |
| PD | Predicate disambiguation | batch_69f72153a9188190b02adc84e1be4af8 |
completed | May 3, 2026, 10:20 a.m. |
Created at: April 26, 2026, 8:19 p.m.