Triple
T12128392
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | INSAT-3D |
E288867
|
entity |
| Predicate | SARSystem |
P103542
|
FINISHED |
| Object | COSPAS-SARSAT compatible |
—
|
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: COSPAS-SARSAT compatible | Statement: [INSAT-3D, SARSystem, COSPAS-SARSAT compatible]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: SARSystem Context triple: [INSAT-3D, SARSystem, COSPAS-SARSAT compatible]
-
A.
sightingSystem
Indicates a relationship where a system is used to detect, observe, or track targets or objects, typically for monitoring or aiming purposes.
-
B.
radarModel
Indicates that one entity is a radar system and the other is the specific model or type designation of that radar.
-
C.
satelliteSystem
Indicates a relationship where one system functions as a satellite or subordinate system orbiting, supporting, or depending on another primary system.
-
D.
radarEquipment
Indicates that one entity is radar equipment used for detecting, tracking, or measuring objects relative to another entity.
-
E.
radarType
Indicates the specific category or classification of radar associated with an entity.
- 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_69d6ab4b5e4c81909950b17151eb0951 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d91841615c819097f20a7447a1b8f4 |
completed | April 10, 2026, 3:33 p.m. |
| PD | Predicate disambiguation | batch_69d91508f8008190b3a90ec0bf0953ca |
completed | April 10, 2026, 3:19 p.m. |
| PDg | Predicate description generation | batch_69d9183ec1008190b437b7d5e1f52830 |
completed | April 10, 2026, 3:33 p.m. |
Created at: April 8, 2026, 9:49 p.m.