Triple
T24842684
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chrysanthine notation |
E621656
|
entity |
| Predicate | notationSystemLevel |
P157404
|
FINISHED |
| Object | reform of earlier Byzantine notation |
—
|
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: reform of earlier Byzantine notation | Statement: [Chrysanthine notation, notationSystemLevel, reform of earlier Byzantine notation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notationSystemLevel Context triple: [Chrysanthine notation, notationSystemLevel, reform of earlier Byzantine notation]
-
A.
notationSystem
Indicates a relationship where one entity is the system or method of notation used to represent or encode another entity.
-
B.
notationType
Indicates the specific system or style of notation used to represent or encode something (such as music, math, or language).
-
C.
levelNotation
Indicates the specific symbolic or textual notation used to represent the level, degree, or rank of something within a defined scale or hierarchy.
-
D.
notationLanguage
Indicates the language or symbolic system in which a notation or formal representation is expressed.
-
E.
notation
Indicates a conventional way of symbolically representing or writing something, such as concepts, quantities, or operations, within a specific system.
- 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_69e2fac185d48190a0a6073ad1f6b792 |
completed | April 18, 2026, 3:30 a.m. |
| NER | Named-entity recognition | batch_69f43043512481909501a3979cac9947 |
completed | May 1, 2026, 4:46 a.m. |
| PD | Predicate disambiguation | batch_69f420fd375c81908ea4a4e60b76ee8f |
completed | May 1, 2026, 3:41 a.m. |
| PDg | Predicate description generation | batch_69f4303fad6c8190844f069164f0904d |
completed | May 1, 2026, 4:46 a.m. |
Created at: April 18, 2026, 5:19 a.m.