Triple
T94149
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Filioque clause in the Nicene Creed |
E1892
|
entity |
| Predicate | hasLiteralMeaning |
P3918
|
FINISHED |
| Object | and from the Son |
—
|
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: and from the Son | Statement: [Filioque clause in the Nicene Creed, hasLiteralMeaning, and from the Son]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLiteralMeaning Context triple: [Filioque clause in the Nicene Creed, hasLiteralMeaning, and from the Son]
-
A.
hasSignificantLanguage
Indicates that an entity possesses a language that plays an important or primary role in its communication, identity, or functioning.
-
B.
hasEndonym
Indicates that an entity has a name or designation used by native speakers or within its own local language or community.
-
C.
hasFullForm
Indicates that one entity is the complete, expanded, or unabbreviated form of another entity.
-
D.
hasBasicLetters
Indicates that an entity contains or is composed of fundamental alphabetic characters, without additional symbols or diacritics.
-
E.
hasRepresentationIn
Indicates that one entity is represented, depicted, or encoded within another entity, such as a concept, object, or data structure having a corresponding representation in a specific medium or context.
- 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_69a24d4862f881908cc8b89d3a78031d |
completed | Feb. 28, 2026, 2:04 a.m. |
| NER | Named-entity recognition | batch_69a24feef1b08190bb9525f71cce053e |
completed | Feb. 28, 2026, 2:16 a.m. |
| PD | Predicate disambiguation | batch_69a24ebb3da08190a8b82564f33cde3b |
completed | Feb. 28, 2026, 2:11 a.m. |
| PDg | Predicate description generation | batch_69a24fed6b8c819080a6c0cd3b16e6bd |
completed | Feb. 28, 2026, 2:16 a.m. |
Created at: Feb. 28, 2026, 2:09 a.m.