Triple
T12579765
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Venera 9 |
E300302
|
entity |
| Predicate | surfaceImagingMethod |
P52562
|
FINISHED |
| Object | television camera system |
—
|
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: television camera system | Statement: [Venera 9, surfaceImagingMethod, television camera system]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: surfaceImagingMethod Context triple: [Venera 9, surfaceImagingMethod, television camera system]
-
A.
imagedBy
Indicates that something is captured, recorded, or represented in an image created by a particular imaging device, method, or agent.
-
B.
imagedIn
Indicates that one entity appears within or is depicted in an image associated with another entity.
-
C.
imagingInstrument
Indicates that a particular instrument or device is used to capture or produce an image of a target or subject.
-
D.
hasImagingType
chosen
Indicates the specific imaging modality or technique associated with or used in a given imaging procedure or result.
-
E.
imageFormation
Indicates the process or mechanism by which an image is generated, captured, or rendered from a scene or source.
- 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_69d7bde87b648190bcd0266e9efde098 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d954e6e20481908bca684c4b497c48 |
completed | April 10, 2026, 7:52 p.m. |
| PD | Predicate disambiguation | batch_69d95416cbd88190b2c65196162349bc |
completed | April 10, 2026, 7:48 p.m. |
Created at: April 9, 2026, 5 p.m.