Triple
T26567937
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Diatessaron |
E666741
|
entity |
| Predicate | usedAsStandardGospelTextIn |
P174241
|
FINISHED |
| Object | Syriac churches |
—
|
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: Syriac churches | Statement: [Diatessaron, usedAsStandardGospelTextIn, Syriac churches]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedAsStandardGospelTextIn Context triple: [Diatessaron, usedAsStandardGospelTextIn, Syriac churches]
-
A.
isGospelInfluenced
Indicates that one entity (such as a work, style, or performance) is influenced in its characteristics, form, or content by gospel music or gospel traditions.
-
B.
languageOfGospelTraditionally
Indicates the language in which a particular Gospel is traditionally believed or held to have been written or transmitted.
-
C.
gospelReadingFrom
Indicates that a particular gospel reading is taken from or sourced in a specified scriptural passage or book.
-
D.
gospelChapter
Indicates that one entity is a specific chapter within a particular gospel text or book.
-
E.
gospelTerm
Indicates that one entity is a term, concept, or expression specifically associated with the gospel or gospel-related discourse in relation to another entity.
- 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_69ee9cfa21c081909e4e36e087debfc6 |
completed | April 26, 2026, 11:17 p.m. |
| NER | Named-entity recognition | batch_69f6bcc425588190afd0dceba43ed79f |
completed | May 3, 2026, 3:11 a.m. |
| PD | Predicate disambiguation | batch_69f6ba6b1e6c8190adf9d6a257e0b744 |
completed | May 3, 2026, 3 a.m. |
| PDg | Predicate description generation | batch_69f6bbf5a8288190ae170bcbe8ab65cf |
completed | May 3, 2026, 3:07 a.m. |
Created at: April 27, 2026, 1:56 a.m.