Triple
T4706430
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | DJI |
E104398
|
entity |
| Predicate | notableProductLine |
P3585
|
FINISHED |
| Object | DJI FPV |
E104398
|
NE 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: DJI FPV | Statement: [DJI, notableProductLine, DJI FPV]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: DJI FPV Context triple: [DJI, notableProductLine, DJI FPV]
-
A.
DJI
chosen
DJI is a leading Chinese technology company best known worldwide for manufacturing consumer and professional drones and aerial imaging systems.
-
B.
^DJI
^DJI is the ticker symbol for the Dow Jones Industrial Average, a major U.S. stock market index tracking 30 large, publicly traded blue-chip companies.
-
C.
Tello
Tello is a Spanish-language surname borne by various notable individuals across fields such as archaeology, politics, and sports.
-
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.
Point Grey
Point Grey is a prominent headland and residential neighborhood on Vancouver’s west side, known for its coastal bluffs, beaches, and views over English Bay and the Strait of Georgia.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_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_69be106d1fc08190808c19025c6f37c4 |
completed | March 21, 2026, 3:28 a.m. |
Created at: March 20, 2026, 1:17 p.m.