Triple

T4706434
Position Surface form Disambiguated ID Type / Status
Subject DJI E104398 entity
Predicate notableProductLine P3585 FINISHED
Object DJI Agras
DJI Agras is a series of agricultural drones designed for tasks like crop spraying, seeding, and precision farming.
 E479916 NE FINISHED

How this triple was built (4 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: DJI Agras | Statement: [DJI, notableProductLine, DJI Agras]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: DJI Agras
Context triple: [DJI, notableProductLine, DJI Agras]
  • A. DJI Avata
    DJI Avata is a compact first-person-view (FPV) camera drone designed for immersive, agile flight and stabilized aerial video.
  • B. DJI Inspire
    DJI Inspire is a professional-grade series of camera drones known for advanced aerial cinematography capabilities and high-performance flight features.
  • C. DJI
    DJI is a leading Chinese technology company best known worldwide for manufacturing consumer and professional drones and aerial imaging systems.
  • D. ANKA UAV
    ANKA UAV is a Turkish-made medium-altitude long-endurance unmanned aerial vehicle designed primarily for intelligence, surveillance, and reconnaissance missions.
  • E. Tello
    Tello is a Spanish-language surname borne by various notable individuals across fields such as archaeology, politics, and sports.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: DJI Agras
Triple: [DJI, notableProductLine, DJI Agras]
Generated description
DJI Agras is a series of agricultural drones designed for tasks like crop spraying, seeding, and precision farming.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: DJI Agras
Target entity description: DJI Agras is a series of agricultural drones designed for tasks like crop spraying, seeding, and precision farming.
  • A. DJI Avata
    DJI Avata is a compact first-person-view (FPV) camera drone designed for immersive, agile flight and stabilized aerial video.
  • B. DJI Inspire
    DJI Inspire is a professional-grade series of camera drones known for advanced aerial cinematography capabilities and high-performance flight features.
  • C. DJI
    DJI is a leading Chinese technology company best known worldwide for manufacturing consumer and professional drones and aerial imaging systems.
  • D. ANKA UAV
    ANKA UAV is a Turkish-made medium-altitude long-endurance unmanned aerial vehicle designed primarily for intelligence, surveillance, and reconnaissance missions.
  • E. Tello
    Tello is a Spanish-language surname borne by various notable individuals across fields such as archaeology, politics, and sports.
  • F. None of above. chosen

Provenance (5 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_69bd43eac3c08190af7e4020c6c3704c completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd63e9f0b88190820aa7fba2f91b6e completed March 20, 2026, 3:12 p.m.
NED1 Entity disambiguation (via context triple) batch_69be77845de88190a93f666d8e9faf00 completed March 21, 2026, 10:48 a.m.
NEDg Description generation batch_69be780ae75481909eb49592d052a572 completed March 21, 2026, 10:50 a.m.
NED2 Entity disambiguation (via description) batch_69be783867c481908440f6e92ba5ddb8 completed March 21, 2026, 10:51 a.m.
Created at: March 20, 2026, 1:17 p.m.