Triple
T810831
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dow Jones Industrial Average |
E17539
|
entity |
| Predicate | dataVendorCode |
P508
|
FINISHED |
| Object | DJI |
E97814
|
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 | Statement: [Dow Jones Industrial Average, dataVendorCode, DJI]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: DJI Context triple: [Dow Jones Industrial Average, dataVendorCode, DJI]
-
A.
^DJI
chosen
^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.
-
B.
Dyson
Dyson is a surname most famously associated with theoretical physicist and mathematician Freeman Dyson, known for his influential work in quantum electrodynamics and futurism.
-
C.
Mobvoi
Mobvoi is a Chinese artificial intelligence company best known for its TicWatch line of smartwatches and other wearable devices.
-
D.
Huawei
Huawei is a major Chinese multinational technology company best known globally for its telecommunications equipment, smartphones, and role in 5G network infrastructure.
-
E.
Panasonic
Panasonic is a major Japanese multinational electronics company known for its wide range of consumer electronics, home appliances, and industrial solutions.
- 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_69a4937ae8a08190b5084a03d532b30e |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4ab282fe48190a05ee97550843cd7 |
completed | March 1, 2026, 9:10 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a7a3b47ba481908a8db2bec414a3e4 |
completed | March 4, 2026, 3:15 a.m. |
Created at: March 1, 2026, 7:38 p.m.