Triple
T6369098
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | DRDO Netra AEW&CS |
E143301
|
entity |
| Predicate | radarCoverage |
P32751
|
FINISHED |
| Object | 240 degrees |
—
|
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: 240 degrees | Statement: [DRDO Netra AEW&CS, radarCoverage, 240 degrees]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: radarCoverage Context triple: [DRDO Netra AEW&CS, radarCoverage, 240 degrees]
-
A.
radarEquipment
Indicates that one entity is radar equipment used for detecting, tracking, or measuring objects relative to another entity.
-
B.
radarType
Indicates the specific category or classification of radar associated with an entity.
-
C.
radarLocation
Indicates the geographic position where a radar system is installed or operating.
-
D.
azimuthCoverage
chosen
Indicates the range or extent of directional angles (azimuths) over which something, such as a sensor or system, provides coverage or operates.
-
E.
radarModel
Indicates that one entity is a radar system and the other is the specific model or type designation of that radar.
- 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_69c008d8c61081908bcaf61510d881ed |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c068265a7481908571be7ea4ac11b7 |
completed | March 22, 2026, 10:07 p.m. |
| PD | Predicate disambiguation | batch_69c060ee055081908c79a1d151bd74cd |
completed | March 22, 2026, 9:36 p.m. |
Created at: March 22, 2026, 4:33 p.m.