Triple
T31154671
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Byzantine echoi |
E794168
|
entity |
| Predicate | notationalMarker |
P6184
|
FINISHED |
| Object | modal signatures in 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: modal signatures in Byzantine notation | Statement: [Byzantine echoi, notationalMarker, modal signatures in Byzantine notation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notationalMarker Context triple: [Byzantine echoi, notationalMarker, modal signatures in Byzantine notation]
-
A.
markingFeature
Indicates a feature that serves as a distinguishing mark or identifier associated with an entity.
-
B.
marksOn
Indicates that one entity bears visible signs, traces, or imprints that have been made or left by another entity.
-
C.
distinctiveMarking
Indicates that one entity bears a unique or distinguishing visual feature or pattern that sets it apart from others.
-
D.
markingDefinition
Indicates that one entity defines the marking, labeling, or classification rules that are applied to another entity.
-
E.
notation
chosen
Indicates a conventional way of symbolically representing or writing something, such as concepts, quantities, or operations, within a specific system.
- 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_69f224d41bb48190a5621cd1485e3a30 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f69c234d648190a243fb2b107136a9 |
completed | May 3, 2026, 12:51 a.m. |
| PD | Predicate disambiguation | batch_69f69665cd9c819088c388fc82fec42e |
completed | May 3, 2026, 12:27 a.m. |
Created at: April 29, 2026, 9:06 p.m.