Triple
T19020022
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Telescopii |
E465458
|
entity |
| Predicate | partOfNotationSystem |
P6517
|
FINISHED |
| Object | Bayer-style stellar naming conventions |
—
|
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: Bayer-style stellar naming conventions | Statement: [Telescopii, partOfNotationSystem, Bayer-style stellar naming conventions]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: partOfNotationSystem Context triple: [Telescopii, partOfNotationSystem, Bayer-style stellar naming conventions]
-
A.
typicalNotation
Indicates that one entity is the standard or commonly used symbolic representation (notation) for another entity.
-
B.
appearsInNotation
Indicates that one entity is represented, referenced, or depicted within the formal notation or symbolic system associated with another entity.
-
C.
usesMusicalSystem
Indicates that one entity employs or operates according to a particular musical system, framework, or set of musical rules.
-
D.
notationSystem
chosen
Indicates a relationship where one entity is the system or method of notation used to represent or encode another entity.
-
E.
distinguishingNotation
Indicates that one entity uses a specific notation or symbol to distinguish or differentiate another entity from similar ones.
- 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_69d8dd025c188190a1d81f5b4ec7e2c6 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5d6ddc9608190a1daec9ddcc79a7a |
completed | April 20, 2026, 7:33 a.m. |
| PD | Predicate disambiguation | batch_69e4a2fd80c081908237317a3a883e1c |
completed | April 19, 2026, 9:40 a.m. |
Created at: April 10, 2026, 12:02 p.m.