Triple

T12878031
Position Surface form Disambiguated ID Type / Status
Subject Carl Ludwig Long E308014 entity
Predicate givenName P17 FINISHED
Object Carl
Carl is the given name of Carl Ludwig Long, a German long jumper best known for winning the silver medal at the 1936 Berlin Olympics and famously befriending Jesse Owens.
 E1007772 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: Carl | Statement: [Carl Ludwig Long, givenName, Carl]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Carl
Context triple: [Carl Ludwig Long, givenName, Carl]
  • A. Carl
    Carl is the given name of Carl Sagan, the renowned American astronomer, science communicator, and author.
  • B. Carl
    Carl is the given name of the influential American microbiologist Carl Woese, known for defining the Archaea domain of life.
  • C. Carl
    Carl is the given name of Carl von Martius, a notable 19th-century German botanist and explorer known for his extensive studies of Brazilian flora.
  • D. Carl
    Carl is the given name of Carl Bosch, the German chemist and engineer who pioneered high-pressure industrial chemistry and shared the 1931 Nobel Prize in Chemistry.
  • E. Carl
    Carl is the given name of the German Romantic composer and conductor Carl Maria von Weber, known for works such as the opera "Der Freischütz."
  • 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: Carl
Triple: [Carl Ludwig Long, givenName, Carl]
Generated description
Carl is the given name of Carl Ludwig Long, a German long jumper best known for winning the silver medal at the 1936 Berlin Olympics and famously befriending Jesse Owens.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Carl
Target entity description: Carl is the given name of Carl Ludwig Long, a German long jumper best known for winning the silver medal at the 1936 Berlin Olympics and famously befriending Jesse Owens.
  • A. Carl
    Carl is the given name of Carl von Schirach, a historical figure associated with Nazi Germany.
  • B. Carl
    Carl is the given name of Carl Gotthard Langhans, the Prussian architect best known for designing Berlin’s Brandenburg Gate.
  • C. Carl
    Carl is the given name of Carl von Linde, the German engineer and inventor known for pioneering refrigeration and gas liquefaction technologies.
  • D. Carl
    Carl is a masculine given name of Germanic origin that is related to Charles and commonly used in many English-speaking and European countries.
  • E. Carl
    Carl is the given name of Carl Bosch, the German chemist and engineer who pioneered high-pressure industrial chemistry and shared the 1931 Nobel Prize in Chemistry.
  • 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_69d7bdf69bc48190af6c2621f28ca351 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d970fa8474819086a8af3c90f3ca84 completed April 10, 2026, 9:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69f69bba33c081909c0050ff7b868a8e completed May 3, 2026, 12:50 a.m.
NEDg Description generation batch_69f69df1032881909255e506ddfd9c9f completed May 3, 2026, 12:59 a.m.
NED2 Entity disambiguation (via description) batch_69f69ea645a0819095edc112b9ed9bff completed May 3, 2026, 1:02 a.m.
Created at: April 9, 2026, 5:38 p.m.