Triple
T861696
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | S.J. |
E18611
|
entity |
| Predicate | usedInCountries |
P20284
|
FINISHED |
| Object | countries with Jesuit presence |
—
|
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: countries with Jesuit presence | Statement: [S.J., usedInCountries, countries with Jesuit presence]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedInCountries Context triple: [S.J., usedInCountries, countries with Jesuit presence]
-
A.
usedInCountry
Indicates that something is utilized, applied, or in operation within the specified country.
-
B.
displayedInCountry
Indicates that something is shown, exhibited, or made visible within the boundaries of a specified country.
-
C.
usedInRegion
Indicates that something is utilized or applied within a specific geographic or administrative region.
-
D.
usedWorldwide
Indicates that something is utilized or applied across many countries or regions around the world.
-
E.
soldInCountry
Indicates that a product or item is offered for sale or has been sold within a specified country.
- 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_69a4938ce8688190a24bdfef82ba7d21 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4ac6631408190a19b83126fa86100 |
completed | March 1, 2026, 9:15 p.m. |
| PD | Predicate disambiguation | batch_69a4aa84835081908aaf98b10656d7d6 |
completed | March 1, 2026, 9:07 p.m. |
| PDg | Predicate description generation | batch_69a4ab498bb0819080e3afb684b504b6 |
completed | March 1, 2026, 9:10 p.m. |
Created at: March 1, 2026, 7:39 p.m.