Triple
T30811698
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Republic of Guinea |
E784660
|
entity |
| Predicate | percentageMuslimApprox |
P17221
|
FINISHED |
| Object | >80% |
—
|
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: >80% | Statement: [Republic of Guinea, percentageMuslimApprox, >80%]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: percentageMuslimApprox Context triple: [Republic of Guinea, percentageMuslimApprox, >80%]
-
A.
populationShareOfMuslims
chosen
Indicates the proportion of a given population that is composed of Muslims.
-
B.
shareReligiousDemographics
Indicates that two entities have similar or identical distributions of religious affiliations within their populations.
-
C.
hasApproximateAdherents
Indicates that an entity is associated with a non-exact, estimated number of adherents or followers.
-
D.
religionSignificantMinorityRegion
Indicates that a particular religion constitutes a significant minority presence within a specified geographic region.
-
E.
numberOfMuslimFightersApprox
Indicates an approximate count of fighters who are identified as Muslim in a given context or event.
- 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_69f224b4eda48190bd212ce4f3901e56 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f6b49436b0819094e21603054d05d4 |
completed | May 3, 2026, 2:36 a.m. |
| PD | Predicate disambiguation | batch_69f6b3a7bdb481908d16a32f49e38c2c |
completed | May 3, 2026, 2:32 a.m. |
Created at: April 29, 2026, 8:43 p.m.