Triple
T19275984
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Saint John's Abbey |
E482054
|
entity |
| Predicate | hasPrimaryLanguageOfLiturgy |
P3115
|
FINISHED |
| Object | English |
—
|
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: English | Statement: [Saint John's Abbey, hasPrimaryLanguageOfLiturgy, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPrimaryLanguageOfLiturgy Context triple: [Saint John's Abbey, hasPrimaryLanguageOfLiturgy, English]
-
A.
usesPrimaryLiturgicalLanguageHistorically
Indicates that an entity has historically used a particular primary liturgical language in its religious rites or worship practices.
-
B.
languageOfWorship
chosen
Indicates the language in which religious worship, rituals, or liturgical practices are conducted.
-
C.
hasPrimaryLiturgicalForm
Indicates that an entity is associated with its main or officially recognized liturgical form used in worship or religious practice.
-
D.
hasClericalLanguage
Indicates that something is expressed using formal, religious, or church-related language or terminology.
-
E.
hasPrimaryLanguage1
Indicates that an entity’s main or most commonly used language is the specified language.
- 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_69d8e8ce54cc8190998418ff1f66ef28 |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e5fbbbdf3481909abb46c71f64106a |
completed | April 20, 2026, 10:11 a.m. |
| PD | Predicate disambiguation | batch_69e4dd07a7208190afcd51ba1dc87c33 |
completed | April 19, 2026, 1:47 p.m. |
Created at: April 10, 2026, 1:29 p.m.