Triple
T1980607
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | BMW X7 |
E43016
|
entity |
| Predicate | brand |
P1500
|
FINISHED |
| Object | BMW |
E10671
|
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: BMW | Statement: [BMW X7, brand, BMW]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: BMW Context triple: [BMW X7, brand, BMW]
-
A.
BMW
chosen
BMW is a German luxury automobile and motorcycle manufacturer renowned for its performance-oriented vehicles and engineering.
-
B.
Audi
Audi is a German luxury automobile manufacturer known for its premium vehicles, advanced engineering, and signature quattro all-wheel-drive technology.
-
C.
BMW Welt
BMW Welt is a futuristic multi-use exhibition, delivery, and event center in Munich that showcases BMW Group vehicles and technology.
-
D.
BMWK
BMWK is the German Federal Ministry responsible for economic policy and climate action at the national level.
-
E.
BMW X Series
The BMW X Series is a lineup of BMW’s luxury crossover and sport utility vehicles known for combining premium comfort with sporty performance and all-wheel-drive capability.
- 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_69a88713ddc88190a969715658ebe7a8 |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abb7c87bc081908ed179d1ca94fa3b |
completed | March 7, 2026, 5:29 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae0ad2a3888190a93e54b53a071afc |
completed | March 8, 2026, 11:48 p.m. |
Created at: March 4, 2026, 7:37 p.m.