Triple
T23009651
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 59 Cygni |
E572871
|
entity |
| Predicate | binarySeparationDetection |
P90051
|
FINISHED |
| Object | not visually resolved |
—
|
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: not visually resolved | Statement: [59 Cygni, binarySeparationDetection, not visually resolved]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: binarySeparationDetection Context triple: [59 Cygni, binarySeparationDetection, not visually resolved]
-
A.
imageSeparationMethod
chosen
Indicates the technique or process used to separate or distinguish different components, regions, or elements within an image.
-
B.
separationMethod
Indicates the technique or process used to separate one substance, component, or entity from another.
-
C.
typeOfSeparation
Indicates the specific manner or category of separation that exists or occurred between entities.
-
D.
separationProcess
Indicates a process in which components of a mixture or system are divided or isolated from one another based on differing properties or conditions.
-
E.
separatesPhase
Indicates that one entity causes or defines a division between different phases or states of another entity or process.
- 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_69e245b764cc8190a51be76f1d9611e1 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f18359f5548190b15a139eb09e30a0 |
completed | April 29, 2026, 4:04 a.m. |
| PD | Predicate disambiguation | batch_69ef3b9cd5488190bcd23183179f48cd |
completed | April 27, 2026, 10:34 a.m. |
Created at: April 17, 2026, 3:51 p.m.