Triple
T12577703
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lanao del Sur |
E300251
|
entity |
| Predicate | isPredominantlyMuslim |
P2986
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Lanao del Sur, isPredominantlyMuslim, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isPredominantlyMuslim Context triple: [Lanao del Sur, isPredominantlyMuslim, true]
-
A.
populationShareOfMuslims
Indicates the proportion of a given population that is composed of Muslims.
-
B.
majorityReligionInUrbanAreas
Indicates that a specified religion is the predominant or most widely practiced faith within the urban areas of a given region or population.
-
C.
religionSignificantMinorityRegion
Indicates that a particular religion constitutes a significant minority presence within a specified geographic region.
-
D.
ethnicReligionMix
Indicates a relationship where a group or context involves a combined or overlapping presence of specific ethnic identities and religious affiliations.
-
E.
dominantReligion
chosen
Indicates the religion that holds primary or majority status within a given group, region, or entity.
- 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_69d7bde87b648190bcd0266e9efde098 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d9550d84908190aea0f50055f6d92e |
completed | April 10, 2026, 7:52 p.m. |
| PD | Predicate disambiguation | batch_69d95414692881909c52a1de7d224b44 |
completed | April 10, 2026, 7:48 p.m. |
Created at: April 9, 2026, 4:53 p.m.