Triple
T4512771
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | International Society for Krishna Consciousness |
E102087
|
entity |
| Predicate | numberOfCountriesActiveIn |
P56465
|
FINISHED |
| Object | over 100 |
—
|
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: over 100 | Statement: [International Society for Krishna Consciousness, numberOfCountriesActiveIn, over 100]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfCountriesActiveIn Context triple: [International Society for Krishna Consciousness, numberOfCountriesActiveIn, over 100]
-
A.
numberOfCurrentNations
Indicates the total count of nations that currently exist or are recognized at a given point in time.
-
B.
numberOfParticipatingNations
Indicates the total count of nations that take part in a specified event, activity, or context.
-
C.
hasNumberOfCountries
Indicates the relationship that specifies how many countries are associated with or contained within a given entity.
-
D.
countryRepresentedCount
chosen
Indicates the number of distinct countries that are represented or associated with a given entity.
-
E.
mostTeamsInCountry
Indicates that an entity has the highest number of teams located within a given country compared to all other entities.
- 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_69bd43d6251c81909deecce3e6e9d69c |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd5722d8fc81909c5f2d9a38d17a6b |
completed | March 20, 2026, 2:18 p.m. |
| PD | Predicate disambiguation | batch_69bd5218afb4819087c99e0a1f22e137 |
completed | March 20, 2026, 1:56 p.m. |
Created at: March 20, 2026, 1:02 p.m.