Triple

T1869405
Position Surface form Disambiguated ID Type / Status
Subject RFC 6020 E38999 entity
Predicate defines P264 FINISHED
Object YANG E210696 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: YANG | Statement: [RFC 6020, defines, YANG]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: YANG
Context triple: [RFC 6020, defines, YANG]
  • A. YANG chosen
    YANG is a data modeling language widely used in networking, particularly with NETCONF and RESTCONF, to define the structure and semantics of configuration and state data on network devices.
  • B. Yang
    Yang is a common Chinese surname with deep historical roots and widespread use across Chinese-speaking communities.
  • C. YANG modeling language
    YANG modeling language is a data modeling language used to define the structure and configuration of network devices and services, particularly in modern network management and automation systems.
  • D. YV
    YV is the IATA airline designator used to identify Mesa Airlines in flight schedules and ticketing systems.
  • E. YOW
    YOW is the three-letter IATA airport code for Ottawa Macdonald–Cartier International Airport, the primary airport serving Canada’s capital city, Ottawa.
  • 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_69a8862f7074819096afe7fe65e179e9 completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69abb0b7e4548190a3761133fbbb7b81 completed March 7, 2026, 4:59 a.m.
NED1 Entity disambiguation (via context triple) batch_69adeae06e5c8190b20cce9c047f6087 completed March 8, 2026, 9:32 p.m.
Created at: March 4, 2026, 7:34 p.m.