Triple
T20479109
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Inverness Corona |
E502402
|
entity |
| Predicate | hostBodyInstanceOf |
P140253
|
FINISHED |
| Object | natural satellite |
—
|
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: natural satellite | Statement: [Inverness Corona, hostBodyInstanceOf, natural satellite]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hostBodyInstanceOf Context triple: [Inverness Corona, hostBodyInstanceOf, natural satellite]
-
A.
hostBodyType
Indicates the type or classification of the body that serves as a host for another entity or process.
-
B.
hasBodyOf
Indicates that one entity possesses, contains, or is composed of the physical body or main substance of another entity.
-
C.
hostsBody
Indicates that one entity serves as the physical container or location in which another entity resides or is situated.
-
D.
includesTypeOfBody
Indicates that one entity encompasses or contains another entity classified as a specific type of body (e.g., physical, celestial, or organizational body).
-
E.
instanceOf
relation of type constraints
- 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_69e0b4af32848190aea80682b44d5d6e |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e69b54c8188190a71e35fab8d194a6 |
completed | April 20, 2026, 9:32 p.m. |
| PD | Predicate disambiguation | batch_69e5768372988190b08ef8ae67d42ab6 |
completed | April 20, 2026, 12:42 a.m. |
| PDg | Predicate description generation | batch_69e58d766b408190a1d3698145fb6d30 |
completed | April 20, 2026, 2:20 a.m. |
Created at: April 16, 2026, 11:34 a.m.