Triple
T35858066
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Magellan |
E1036561
|
entity |
| Predicate | radarResolution |
P25684
|
FINISHED |
| Object | about 100 to 300 meters |
—
|
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: about 100 to 300 meters | Statement: [Magellan, radarResolution, about 100 to 300 meters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: radarResolution Context triple: [Magellan, radarResolution, about 100 to 300 meters]
-
A.
radarConfiguration
Indicates a relationship where a radar system is associated with or defined by a specific configuration or setup of its operational parameters.
-
B.
radarFunction
Indicates that one entity serves as the functional role, purpose, or operational capability of a radar system in relation to another entity.
-
C.
radarType
Indicates the specific category or classification of radar associated with an entity.
-
D.
samplingResolution
Indicates the level of detail or granularity at which data is sampled or measurements are taken in a process or system.
-
E.
hasSpatialResolution
chosen
Indicates that something is characterized by a specific level of spatial detail or granularity at which it can represent or distinguish features in space.
- 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_69f76e1b4aa481909630373171eb5ec6 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7aa3883d48190b05e3d2da7a017ae |
completed | May 3, 2026, 8:04 p.m. |
| PD | Predicate disambiguation | batch_69f7a8d435288190b30b1991fb003121 |
completed | May 3, 2026, 7:58 p.m. |
Created at: May 3, 2026, 4:06 p.m.