Triple
T26568001
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | compiling the Diatessaron |
E666742
|
entity |
| Predicate | hasTextualImpact |
P171405
|
FINISHED |
| Object | influencing later Syriac gospel manuscripts |
—
|
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: influencing later Syriac gospel manuscripts | Statement: [compiling the Diatessaron, hasTextualImpact, influencing later Syriac gospel manuscripts]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTextualImpact Context triple: [compiling the Diatessaron, hasTextualImpact, influencing later Syriac gospel manuscripts]
-
A.
hasVisualImpact
Indicates that one entity affects or influences the visual appearance or aesthetic perception of another.
-
B.
hasEffectText
Indicates that a subject is associated with a textual description specifying its effect or impact.
-
C.
encodingImpact
Indicates how one encoding or encoding choice affects, modifies, or constrains another process, representation, or outcome.
-
D.
canImpact
Indicates that one entity has the potential or ability to affect, influence, or cause a change in another entity.
-
E.
hasImpactScale
Indicates the degree or magnitude of impact that one entity or action has on another, typically expressed along a defined scale.
- 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_69f69f80b62c8190bf2af2be0d3a7df8 |
completed | May 3, 2026, 1:06 a.m. |
| PD | Predicate disambiguation | batch_69f69d17e8d48190b30bcc2f4bd81eb2 |
completed | May 3, 2026, 12:55 a.m. |
| PDg | Predicate description generation | batch_69f69edae2448190925ce701c8792c52 |
completed | May 3, 2026, 1:03 a.m. |
Created at: April 27, 2026, 1:56 a.m.