Triple
T31870549
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mohammad |
E813584
|
entity |
| Predicate | frequencyAmongMuslims |
P174964
|
FINISHED |
| Object | very high |
—
|
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: very high | Statement: [Mohammad, frequencyAmongMuslims, very high]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: frequencyAmongMuslims Context triple: [Mohammad, frequencyAmongMuslims, very high]
-
A.
populationShareOfMuslims
Indicates the proportion of a given population that is composed of Muslims.
-
B.
strengthMuslims
Indicates a relationship where strength, power, or resilience is attributed to, associated with, or exercised by Muslims.
-
C.
ethnicReligionMix
Indicates a relationship where a group or context involves a combined or overlapping presence of specific ethnic identities and religious affiliations.
-
D.
numberOfImams
Indicates the count of distinct imams associated with or relevant to a given entity or context.
-
E.
ethnicReligion
Indicates that a religion is closely associated with a particular ethnic group, often tied to that group’s culture, ancestry, or identity.
- 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_69f348ecb07481909c8f72619131b115 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69f6cd9bae8c8190b528641499162a75 |
completed | May 3, 2026, 4:22 a.m. |
| PD | Predicate disambiguation | batch_69f6cc1470808190b70cdfd7a6395670 |
completed | May 3, 2026, 4:16 a.m. |
| PDg | Predicate description generation | batch_69f6cd119cac8190a0b3ebe8b9c742c2 |
completed | May 3, 2026, 4:20 a.m. |
Created at: April 30, 2026, 11:54 p.m.