Triple
T29918899
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | United Methodist general agencies |
E759865
|
entity |
| Predicate | mayOperateInLanguages |
P35567
|
FINISHED |
| Object | multiple languages depending on region |
—
|
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: multiple languages depending on region | Statement: [United Methodist general agencies, mayOperateInLanguages, multiple languages depending on region]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mayOperateInLanguages Context triple: [United Methodist general agencies, mayOperateInLanguages, multiple languages depending on region]
-
A.
mayUseLanguagesOf
Indicates that an entity is permitted to use the languages associated with another entity.
-
B.
hasLanguages
chosen
Indicates that an entity is associated with one or more languages it uses, supports, or is expressed in.
-
C.
hasPrimaryLanguageOfOperations
Indicates that an entity conducts its main activities or operations primarily using a specified language.
-
D.
tertiaryLanguageOfOperation
Indicates that an entity uses a specified language as its third most prominent or prioritized language of operation.
-
E.
usesWorkingLanguagesOf
Indicates that one entity employs or operates using the working languages associated with another 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_69f2246189fc8190996b63ee1f9a2374 |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_69f6779140408190987216918cfaf0cb |
completed | May 2, 2026, 10:15 p.m. |
| PD | Predicate disambiguation | batch_69f66ec8298c8190b41fe9d182c05676 |
completed | May 2, 2026, 9:38 p.m. |
Created at: April 29, 2026, 6:13 p.m.