Triple
T7286725
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | pastoral constitution |
E163887
|
entity |
| Predicate | hasLanguageCharacter |
P75393
|
FINISHED |
| Object | more practical than strictly doctrinal |
—
|
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: more practical than strictly doctrinal | Statement: [pastoral constitution, hasLanguageCharacter, more practical than strictly doctrinal]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLanguageCharacter Context triple: [pastoral constitution, hasLanguageCharacter, more practical than strictly doctrinal]
-
A.
hasLocalCharacter
Indicates that something possesses qualities, features, or significance that are specific to a particular locality or region.
-
B.
hasTextualCharacter
Indicates that something possesses or exhibits the qualities of written or printed text, such as letters, symbols, or characters.
-
C.
isCharacterInWorkLanguage
Indicates that a character appears in a work (e.g., book, film, game) in a specific language version or localization.
-
D.
hasSpecialCharacter
Indicates that a given entity (such as a string or identifier) contains at least one non-alphanumeric special character.
-
E.
hasUnicode
Indicates that an entity is associated with, represented by, or encoded using a specific Unicode character or sequence.
- 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_69c6886093b88190a254b1ce6db8bae7 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6eb532adc8190bcbbf31bb54383fb |
completed | March 27, 2026, 8:40 p.m. |
| PD | Predicate disambiguation | batch_69c6e76c5fbc8190b378830082f11cb0 |
completed | March 27, 2026, 8:24 p.m. |
| PDg | Predicate description generation | batch_69c6e82b0f9881909d29c99af1ea0dbf |
completed | March 27, 2026, 8:27 p.m. |
Created at: March 27, 2026, 2:59 p.m.