Triple

T3516647
Position Surface form Disambiguated ID Type / Status
Subject C. Robert Kehler E74323 entity
Predicate givenName P17 FINISHED
Object C.
C. is the initial of the given name of C. Robert Kehler, a retired United States Air Force general who formerly commanded U.S. Strategic Command.
 E365031 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: C. | Statement: [C. Robert Kehler, givenName, C.]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: C.
Context triple: [C. Robert Kehler, givenName, C.]
  • A. C-2
    C-2 is a commuter rail line within the Cercanías Madrid network that connects central Madrid with its surrounding metropolitan areas.
  • B. C-3
    C-3 is one of the main commuter rail lines in the Cercanías Madrid network, connecting central Madrid with several southern suburbs and surrounding municipalities.
  • C. C-1
    C-1 is a commuter rail line in the Cercanías Madrid network that connects central Madrid with its surrounding metropolitan areas.
  • D. D
    The D is a New York City Subway service that runs on the IND Sixth Avenue Line in Manhattan and connects Rockefeller Center with other major destinations across the city.
  • E. D
    D is a statically typed, compiled systems programming language designed as a modern successor to C and C++, emphasizing high performance, safety features, and programmer productivity.
  • 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: C.
Triple: [C. Robert Kehler, givenName, C.]
Generated description
C. is the initial of the given name of C. Robert Kehler, a retired United States Air Force general who formerly commanded U.S. Strategic Command.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: C.
Target entity description: C. is the initial of the given name of C. Robert Kehler, a retired United States Air Force general who formerly commanded U.S. Strategic Command.
  • A. C-2
    C-2 is a commuter rail line within the Cercanías Madrid network that connects central Madrid with its surrounding metropolitan areas.
  • B. C-3
    C-3 is one of the main commuter rail lines in the Cercanías Madrid network, connecting central Madrid with several southern suburbs and surrounding municipalities.
  • C. C-1
    C-1 is a commuter rail line in the Cercanías Madrid network that connects central Madrid with its surrounding metropolitan areas.
  • D. D
    The D is a New York City Subway service that runs on the IND Sixth Avenue Line in Manhattan and connects Rockefeller Center with other major destinations across the city.
  • E. D
    D is a statically typed, compiled systems programming language designed as a modern successor to C and C++, emphasizing high performance, safety features, and programmer productivity.
  • 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_69ad85cfb5c881909c9a2edd9d6043cc completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adbc31c0688190a890621a901f5f5f completed March 8, 2026, 6:13 p.m.
NED1 Entity disambiguation (via context triple) batch_69b37e7da9c08190ab417b45339513bd completed March 13, 2026, 3:03 a.m.
NEDg Description generation batch_69b37f61b4a88190b36ada98f063edcf completed March 13, 2026, 3:07 a.m.
NED2 Entity disambiguation (via description) batch_69b37fbec2ec81909228716c70ffa2bd completed March 13, 2026, 3:08 a.m.
Created at: March 8, 2026, 3:19 p.m.