Triple
T16120363
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Li Auto |
E391117
|
entity |
| Predicate | competesWith |
P1375
|
FINISHED |
| Object | NIO |
E323034
|
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: NIO | Statement: [Li Auto, competesWith, NIO]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: NIO Context triple: [Li Auto, competesWith, NIO]
-
A.
NIO
chosen
NIO is a Chinese electric vehicle manufacturer known for its premium smart EVs and innovative battery-swapping technology.
-
B.
Nio
Nio is a Chinese electric vehicle manufacturer known for its premium smart EVs and battery-swapping technology.
-
C.
java.nio
java.nio is a Java API package that provides non-blocking I/O, buffer management, and scalable channel-based input/output operations.
-
D.
NIO ES6
The NIO ES6 is a mid-size all-electric SUV from Chinese automaker NIO, known for its premium features, strong performance, and battery-swapping capability.
-
E.
IO
IO is the commonly used abbreviation for the U.S. Department of State’s Bureau of International Organization Affairs, which manages U.S. engagement with international organizations such as the United Nations.
- 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_69d87f1a8dd881909f1de6ef78849874 |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e20200acac8190a47e6a917ff8dd34 |
completed | April 17, 2026, 9:48 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fff2a61e448190be1f8c79cae6c7ee |
completed | May 10, 2026, 2:51 a.m. |
Created at: April 10, 2026, 5 a.m.