Triple
T31280601
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Archdiocese of Chihuahua |
E797655
|
entity |
| Predicate | hasLaityLanguage |
P9278
|
FINISHED |
| Object | Spanish |
—
|
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: Spanish | Statement: [Archdiocese of Chihuahua, hasLaityLanguage, Spanish]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLaityLanguage Context triple: [Archdiocese of Chihuahua, hasLaityLanguage, Spanish]
-
A.
hasClericalLanguage
Indicates that something is expressed using formal, religious, or church-related language or terminology.
-
B.
hasLanguageOfScripture
Indicates that an entity’s scriptural or sacred texts are written or expressed in a specified language.
-
C.
hasLanguageOn
chosen
Indicates that an entity uses or is associated with a particular language in a specific context, medium, or location.
-
D.
liturgicalLanguageVersion
Indicates that one entity is a specific version or form of another entity expressed in a particular liturgical language.
-
E.
languageOfReligion
Indicates the language in which a particular religion is traditionally expressed, practiced, or documented.
- 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_69f224def9088190a37034eab3daf57f |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69fe0d165a48819098b854318a50d76c |
completed | May 8, 2026, 4:19 p.m. |
| PD | Predicate disambiguation | batch_69fe0931002481908a95b34f95e9f64e |
completed | May 8, 2026, 4:02 p.m. |
Created at: April 29, 2026, 9:13 p.m.