Triple
T19933999
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Indian Muslims |
E479127
|
entity |
| Predicate | populationRankInWorld |
P1169
|
FINISHED |
| Object | one of the largest Muslim populations globally |
—
|
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: one of the largest Muslim populations globally | Statement: [Indian Muslims, populationRankInWorld, one of the largest Muslim populations globally]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: populationRankInWorld Context triple: [Indian Muslims, populationRankInWorld, one of the largest Muslim populations globally]
-
A.
populationRank
chosen
Indicates the relative position of an entity in an ordered list based on the size of its population.
-
B.
populationRankAfter
Indicates the relative position of an entity in a population-based ordering that comes after another entity’s population rank.
-
C.
capacityRankInWorld
Indicates the relative position or ranking of an entity’s capacity compared to all similar entities worldwide.
-
D.
countryRanking
Indicates the relative position or rank assigned to a country within a specific ordered list or comparative evaluation.
-
E.
populationDensityRankWorld
Indicates the position of an entity in a global ranking ordered by population density.
- 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_69d8e521855c8190b41871700afc8d6a |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e65a1553348190a6c4004d3f9a57c5 |
completed | April 20, 2026, 4:53 p.m. |
| PD | Predicate disambiguation | batch_69e537f070b481908958e0e5911dcdc1 |
completed | April 19, 2026, 8:15 p.m. |
Created at: April 10, 2026, 1:53 p.m.