Triple

T8413782
Position Surface form Disambiguated ID Type / Status
Subject Apollo DN100 E198683 entity
Predicate targetMarket P481 FINISHED
Object CAE
CAE is a Canadian multinational company specializing in simulation and training solutions, particularly for civil aviation, defense, and healthcare industries.
 E732918 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: CAE | Statement: [Apollo DN100, targetMarket, CAE]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: CAE
Context triple: [Apollo DN100, targetMarket, CAE]
  • A. CAE
    CAE (Computer-Aided Engineering) is the use of computer software to simulate, analyze, and optimize engineering designs and processes.
  • B. CAEATFA
    CAEATFA is a California state agency that provides financing support to promote alternative energy, energy efficiency, and advanced transportation technologies.
  • C. CAI
    CAI is the three-letter IATA airport code for Cairo International Airport, the main international gateway to Cairo, Egypt.
  • D. CIE
    CIE is the post-nominal abbreviation for a Companion of the Order of the Indian Empire, a British order of chivalry established during the period of the British Raj.
  • E. CAES
    CAES is a college-level academic unit focused on education and research in agriculture, environmental sciences, and related fields.
  • 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: CAE
Triple: [Apollo DN100, targetMarket, CAE]
Generated description
CAE is a Canadian multinational company specializing in simulation and training solutions, particularly for civil aviation, defense, and healthcare industries.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: CAE
Target entity description: CAE is a Canadian multinational company specializing in simulation and training solutions, particularly for civil aviation, defense, and healthcare industries.
  • A. CAE
    CAE (Computer-Aided Engineering) is the use of computer software to simulate, analyze, and optimize engineering designs and processes.
  • B. CAEATFA
    CAEATFA is a California state agency that provides financing support to promote alternative energy, energy efficiency, and advanced transportation technologies.
  • C. CAI
    CAI is the three-letter IATA airport code for Cairo International Airport, the main international gateway to Cairo, Egypt.
  • D. CIE
    CIE is the post-nominal abbreviation for a Companion of the Order of the Indian Empire, a British order of chivalry established during the period of the British Raj.
  • E. CAES
    CAES is a college-level academic unit focused on education and research in agriculture, environmental sciences, and related fields.
  • 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_69ca831201b481909e137936ef99ff11 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cb83e328cc8190b3b038005d0bb66f completed March 31, 2026, 8:20 a.m.
NED1 Entity disambiguation (via context triple) batch_69ce032a25ec819094c6346eb2a7f973 completed April 2, 2026, 5:48 a.m.
NEDg Description generation batch_69ce0781859c8190bb92f41c00af459b completed April 2, 2026, 6:06 a.m.
NED2 Entity disambiguation (via description) batch_69ce089d09c08190ba321aed4044a862 completed April 2, 2026, 6:11 a.m.
Created at: March 30, 2026, 6:06 p.m.