Triple
T23567835
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Roman Catholic Mass for the Dead |
E580018
|
entity |
| Predicate | permittedLanguage |
P101345
|
FINISHED |
| Object | vernacular languages |
—
|
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: vernacular languages | Statement: [Roman Catholic Mass for the Dead, permittedLanguage, vernacular languages]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: permittedLanguage Context triple: [Roman Catholic Mass for the Dead, permittedLanguage, vernacular languages]
-
A.
eligibleLanguage
Indicates that a particular language satisfies the required conditions to be considered valid or allowed in a given context.
-
B.
possibleLanguage
Indicates that an entity could plausibly be expressed, interpreted, or communicated in a given language.
-
C.
languageAllowance
chosen
Indicates the extent to which one entity permits or supports the use of a particular language by another entity.
-
D.
requiredLanguage
Indicates that a specific language is necessary or must be used for a given entity, action, or interaction.
-
E.
usesLanguageFor
Indicates that an entity employs a particular language as a tool or medium to perform some activity, function, or purpose.
- 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_69e24601a9108190bc31e83833c980e4 |
completed | April 17, 2026, 2:38 p.m. |
| NER | Named-entity recognition | batch_69f1af6e11008190bdd28c3f85e3004e |
completed | April 29, 2026, 7:12 a.m. |
| PD | Predicate disambiguation | batch_69f118bcc0b08190b25a8dddfd461a0e |
completed | April 28, 2026, 8:29 p.m. |
Created at: April 17, 2026, 6:35 p.m.