Triple
T21739645
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eleona Church |
E536619
|
entity |
| Predicate | languageDisplays |
P145180
|
FINISHED |
| Object | multiple translations of the Lord’s Prayer |
—
|
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 translations of the Lord’s Prayer | Statement: [Eleona Church, languageDisplays, multiple translations of the Lord’s Prayer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageDisplays Context triple: [Eleona Church, languageDisplays, multiple translations of the Lord’s Prayer]
-
A.
languageView
Indicates a relationship where one entity views, interprets, or presents another entity through the lens of a particular language or linguistic perspective.
-
B.
languageVariant
Indicates that one language is a variant, dialect, or localized form of another language.
-
C.
languageSpecifies
Indicates that one entity defines or constrains the syntax, semantics, or usage rules that govern how another language or linguistic system is expressed or interpreted.
-
D.
languageLabel
Indicates the human-readable name or label of a language associated with an entity or resource.
-
E.
languageCategory
Indicates the classification relationship where a language is assigned to a particular linguistic or functional category.
- 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_69e0c46df5448190b4322127ffc4c690 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69f01a714c208190b96efe23ed3bf0db |
completed | April 28, 2026, 2:24 a.m. |
| PD | Predicate disambiguation | batch_69e6969c16fc8190b5126c169317d85d |
completed | April 20, 2026, 9:11 p.m. |
| PDg | Predicate description generation | batch_69e69f3ed4408190a4a78410bf660c44 |
completed | April 20, 2026, 9:48 p.m. |
Created at: April 16, 2026, 6:49 p.m.