Triple
T9535436
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Johannine literature |
E230001
|
entity |
| Predicate | hasDistinctiveStyle |
P18160
|
FINISHED |
| Object | symbolic language |
—
|
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: symbolic language | Statement: [Johannine literature, hasDistinctiveStyle, symbolic language]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDistinctiveStyle Context triple: [Johannine literature, hasDistinctiveStyle, symbolic language]
-
A.
hasDistinctiveShape
Indicates that an entity possesses a shape or form that is notably different from others and can be easily recognized or distinguished.
-
B.
fashionCharacteristic
Indicates a relationship where one entity possesses or exhibits a particular style, trend, or fashion-related attribute in relation to another.
-
C.
styleDiversity
Indicates variation in the manner, form, or approach with which an entity presents, performs, or expresses something across different instances or contexts.
-
D.
hasDesign
Indicates that one entity possesses, embodies, or is characterized by a particular design associated with another entity.
-
E.
hasDistinctFeature
chosen
Indicates that an entity possesses a specific characteristic or attribute that differentiates it from others.
- 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_69ca847b1b3081908f72bc932c17cc41 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd98cd6a5c8190835c0910ec38ede3 |
completed | April 1, 2026, 10:14 p.m. |
| PD | Predicate disambiguation | batch_69cca56c44f88190a54a5d2a133bb07e |
completed | April 1, 2026, 4:56 a.m. |
Created at: March 30, 2026, 8 p.m.