Triple
T4706452
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | DJI |
E104398
|
entity |
| Predicate | hasSubsidiaryBrand |
P25079
|
FINISHED |
| Object | DJI Agriculture |
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 Agriculture | Statement: [DJI, hasSubsidiaryBrand, DJI Agriculture]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: DJI Agriculture Context triple: [DJI, hasSubsidiaryBrand, DJI Agriculture]
-
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.
DG AGRI
DG AGRI is the European Commission department responsible for EU policy on agriculture and rural development, including the Common Agricultural Policy.
-
D.
Liquid Robotics
Liquid Robotics is a marine technology company best known for developing autonomous Wave Glider ocean robots used for long-duration ocean data collection and monitoring.
-
E.
Maxar Technologies
Maxar Technologies is an American space technology and intelligence company known for providing high-resolution Earth imagery, geospatial data, and satellite solutions to government and commercial customers.
- 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.