Triple

T1869387
Position Surface form Disambiguated ID Type / Status
Subject Yet Another Next Generation E38998 entity
Predicate hasAcronym P43 FINISHED
Object YANG
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.
 E210696 NE FINISHED

How this triple was built (4 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: [Yet Another Next Generation, hasAcronym, YANG]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: YANG
Context triple: [Yet Another Next Generation, hasAcronym, YANG]
  • A. Yang
    Yang is a common Chinese surname with deep historical roots and widespread use across Chinese-speaking communities.
  • B. YV
    YV is the IATA airline designator used to identify Mesa Airlines in flight schedules and ticketing systems.
  • C. YOW
    YOW is the three-letter IATA airport code for Ottawa Macdonald–Cartier International Airport, the primary airport serving Canada’s capital city, Ottawa.
  • D. YAKT
    YAKT is the time zone abbreviation for Yakutsk Time, used in parts of eastern Russia.
  • E. YX
    YX is the IATA airline designator used by Republic Airways, a major U.S. regional airline operating flights on behalf of larger carriers.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: YANG
Triple: [Yet Another Next Generation, hasAcronym, YANG]
Generated description
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.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: YANG
Target entity description: 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.
  • A. Yang
    Yang is a common Chinese surname with deep historical roots and widespread use across Chinese-speaking communities.
  • B. YV
    YV is the IATA airline designator used to identify Mesa Airlines in flight schedules and ticketing systems.
  • C. YOW
    YOW is the three-letter IATA airport code for Ottawa Macdonald–Cartier International Airport, the primary airport serving Canada’s capital city, Ottawa.
  • D. YAKT
    YAKT is the time zone abbreviation for Yakutsk Time, used in parts of eastern Russia.
  • E. YX
    YX is the IATA airline designator used by Republic Airways, a major U.S. regional airline operating flights on behalf of larger carriers.
  • F. None of above. chosen

Provenance (5 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_69addf5163d88190a41df4c8f4e196f0 completed March 8, 2026, 8:42 p.m.
NEDg Description generation batch_69ade3146c80819080503bb501abca3a completed March 8, 2026, 8:59 p.m.
NED2 Entity disambiguation (via description) batch_69ade37080fc81908aa4eaf9aded9e59 completed March 8, 2026, 9 p.m.
Created at: March 4, 2026, 7:34 p.m.