Triple

T286922
Position Surface form Disambiguated ID Type / Status
Subject Windows E5904 entity
Predicate programmingLanguage P1592 FINISHED
Object C E9269 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: C | Statement: [Windows, programmingLanguage, C]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: C
Context triple: [Windows, programmingLanguage, C]
  • A. C chosen
    C is a foundational, general-purpose programming language known for its efficiency, low-level memory access, and influence on many later languages such as C++, Java, and Python.
  • B. Terminal C
    Terminal C is one of the main passenger terminals at Luis Muñoz Marín International Airport in Puerto Rico, serving commercial airline operations and traveler services.
  • C. C++
    C++ is a high-performance, general-purpose programming language widely used for system/software development, game engines, and performance-critical applications.
  • D. .cl
    .cl is the country code top-level domain (ccTLD) assigned to Chile for use on the internet.
  • E. CED
    CED is an academic unit focused on the study and practice of environmental design, including fields such as architecture, landscape architecture, and urban planning.
  • 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_69a25946a7ac8190a78871c210213272 completed Feb. 28, 2026, 2:56 a.m.
NER Named-entity recognition batch_69a25e2ddaa88190b08c40b5823f30a0 completed Feb. 28, 2026, 3:17 a.m.
NED1 Entity disambiguation (via context triple) batch_69a3a33a38b08190951aa413588c59e1 completed March 1, 2026, 2:23 a.m.
Created at: Feb. 28, 2026, 3:02 a.m.