Triple

T8755707
Position Surface form Disambiguated ID Type / Status
Subject NETMOD E208067 entity
Predicate standardizes P1371 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: [NETMOD, standardizes, YANG]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: YANG
Context triple: [NETMOD, standardizes, 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. YAM
    YAM is the IATA airport code for Sault Ste. Marie Airport in Ontario, Canada.
  • D. 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.
  • E. YB
    YB is the common abbreviation for BSC Young Boys, a professional football club based in Bern, Switzerland.
  • 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_69ca835cd6b08190bd7c63db92f53c86 completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc5dd95e9481909cc88e8d91601754 completed March 31, 2026, 11:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69cf43305664819085e762e42b138754 completed April 3, 2026, 4:33 a.m.
Created at: March 30, 2026, 6:39 p.m.