Triple

T13526918
Position Surface form Disambiguated ID Type / Status
Subject XPeng E323035 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: [XPeng, competesWith, NIO]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: NIO
Context triple: [XPeng, competesWith, NIO]
  • A. NIO chosen
    NIO is a Chinese electric vehicle manufacturer known for its premium smart EVs and innovative battery-swapping technology.
  • B. java.nio
    java.nio is a Java API package that provides non-blocking I/O, buffer management, and scalable channel-based input/output operations.
  • C. 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.
  • D. i/o
    i/o is a studio album by English musician Peter Gabriel, known for its long-anticipated release and exploration of human connection, technology, and consciousness.
  • E. NIIP
    NIIP is a Russian defense enterprise best known for designing advanced radar and fire-control systems for surface-to-air missile complexes and combat aircraft.
  • 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_69d80766a21881909f21a1b7421d3b8a completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbafb8e0cc8190b47f6aeb8ced470e completed April 12, 2026, 2:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69f76ba9fccc81908ec2e33d66aae8ea completed May 3, 2026, 3:37 p.m.
Created at: April 9, 2026, 9:44 p.m.