Triple

T11439346
Position Surface form Disambiguated ID Type / Status
Subject Italian Alpine Club E271100 entity
Predicate shortName P43 FINISHED
Object CAI
CAI is the commonly used acronym for the Italian Alpine Club, a major national organization dedicated to mountaineering, hiking, and the protection of the Alpine environment in Italy.
 E926646 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: CAI | Statement: [Italian Alpine Club, shortName, CAI]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: CAI
Context triple: [Italian Alpine Club, shortName, CAI]
  • A. CAI
    CAI is the three-letter IATA airport code for Cairo International Airport, the main international gateway to Cairo, Egypt.
  • B. CAE
    CAE (Computer-Aided Engineering) is the use of computer software to simulate, analyze, and optimize engineering designs and processes.
  • C. CAE
    CAE is the IATA airport code for Columbia Metropolitan Airport, the primary commercial airport serving Columbia, South Carolina.
  • D. CAE
    CAE is a Canadian multinational company specializing in simulation and training solutions, particularly for civil aviation, defense, and healthcare industries.
  • E. CADE
    CADE is a leading international conference focused on research and advances in automated reasoning and automated theorem proving.
  • 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: CAI
Triple: [Italian Alpine Club, shortName, CAI]
Generated description
CAI is the commonly used acronym for the Italian Alpine Club, a major national organization dedicated to mountaineering, hiking, and the protection of the Alpine environment in Italy.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: CAI
Target entity description: CAI is the commonly used acronym for the Italian Alpine Club, a major national organization dedicated to mountaineering, hiking, and the protection of the Alpine environment in Italy.
  • A. CAI
    CAI is the three-letter IATA airport code for Cairo International Airport, the main international gateway to Cairo, Egypt.
  • B. CAE
    CAE (Computer-Aided Engineering) is the use of computer software to simulate, analyze, and optimize engineering designs and processes.
  • C. CAE
    CAE is the IATA airport code for Columbia Metropolitan Airport, the primary commercial airport serving Columbia, South Carolina.
  • D. CAE
    CAE is a Canadian multinational company specializing in simulation and training solutions, particularly for civil aviation, defense, and healthcare industries.
  • E. CADE
    CADE is a leading international conference focused on research and advances in automated reasoning and automated theorem proving.
  • 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_69d6aadeef688190874bcecd88b3dd9b completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d80888190c8190b6365550ffe4931c completed April 9, 2026, 8:14 p.m.
NED1 Entity disambiguation (via context triple) batch_69e5d39554c48190969cc0ebd4dbc368 completed April 20, 2026, 7:19 a.m.
NEDg Description generation batch_69e5d91b047c81909ea4c7f114bfbba5 completed April 20, 2026, 7:43 a.m.
NED2 Entity disambiguation (via description) batch_69e5e2de4cd081908d30c44853565029 completed April 20, 2026, 8:25 a.m.
Created at: April 8, 2026, 9:35 p.m.