Triple

T156239
Position Surface form Disambiguated ID Type / Status
Subject Solar System E3187 entity
Predicate hasComponent P35 FINISHED
Object Venus
Venus is the second planet from the Sun, known for its dense, toxic atmosphere, extreme surface temperatures, and bright visibility in Earth's sky.
 E19350 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: Venus | Statement: [Solar System, hasComponent, Venus]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Venus
Context triple: [Solar System, hasComponent, Venus]
  • A. Merkur
    Merkur was a short-lived automotive marque created by Ford in the 1980s to sell European-designed performance and luxury cars in the North American market.
  • B. Venera
    Venera is a grade or class within the Mexican Order of the Aztec Eagle, the country’s highest distinction awarded to foreigners.
  • C. Mercury
    Mercury was an American automobile marque of the Ford Motor Company known for producing mid-priced cars positioned between Ford and Lincoln.
  • D. Mercury
    Mercury is the smallest and innermost planet in our Solar System, known for its extreme temperature variations and heavily cratered surface.
  • E. Vulcan
    Vulcan is the Roman god of fire, metalworking, and the forge, often depicted as a blacksmith crafting weapons and armor for the gods.
  • 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: Venus
Triple: [Solar System, hasComponent, Venus]
Generated description
Venus is the second planet from the Sun, known for its dense, toxic atmosphere, extreme surface temperatures, and bright visibility in Earth's sky.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Venus
Target entity description: Venus is the second planet from the Sun, known for its dense, toxic atmosphere, extreme surface temperatures, and bright visibility in Earth's sky.
  • A. Merkur
    Merkur was a short-lived automotive marque created by Ford in the 1980s to sell European-designed performance and luxury cars in the North American market.
  • B. Venera
    Venera is a grade or class within the Mexican Order of the Aztec Eagle, the country’s highest distinction awarded to foreigners.
  • C. Mercury
    Mercury was an American automobile marque of the Ford Motor Company known for producing mid-priced cars positioned between Ford and Lincoln.
  • D. Mercury
    Mercury is the smallest and innermost planet in our Solar System, known for its extreme temperature variations and heavily cratered surface.
  • E. Vulcan
    Vulcan is the Roman god of fire, metalworking, and the forge, often depicted as a blacksmith crafting weapons and armor for the gods.
  • 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_69a2527757ec819090b8becb2cf1a862 completed Feb. 28, 2026, 2:27 a.m.
NER Named-entity recognition batch_69a2582eb6408190beb38213c7d7d968 completed Feb. 28, 2026, 2:51 a.m.
NED1 Entity disambiguation (via context triple) batch_69a2d0c68468819089f1ebdb4ff46a0c completed Feb. 28, 2026, 11:25 a.m.
NEDg Description generation batch_69a2d16a37c48190ba4f452772407852 completed Feb. 28, 2026, 11:28 a.m.
NED2 Entity disambiguation (via description) batch_69a2d1e0c6d08190a3c78feec70a173b completed Feb. 28, 2026, 11:30 a.m.
Created at: Feb. 28, 2026, 2:31 a.m.