Triple

T37288465
Position Surface form Disambiguated ID Type / Status
Subject Commonwealth Aircraft Corporation E925596 entity
Predicate hasAbbreviation P43 FINISHED
Object CAC
CAC is the abbreviation for the Commonwealth Aircraft Corporation, an Australian company historically known for designing and manufacturing military and civilian aircraft.
E2220570 NE FINISHED

How this triple was built (2 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: CAC | Statement: [Commonwealth Aircraft Corporation, hasAbbreviation, CAC]
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: CAC
Triple: [Commonwealth Aircraft Corporation, hasAbbreviation, CAC]
Generated description
CAC is the abbreviation for the Commonwealth Aircraft Corporation, an Australian company historically known for designing and manufacturing military and civilian aircraft.

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_69f76eafe20c8190856d3b996a4c31a7 completed May 3, 2026, 3:50 p.m.
NER Named-entity recognition batch_69fb5aca86a081908de62716ff45e200 completed May 6, 2026, 3:14 p.m.
NED1 Entity disambiguation (via context triple) batch_6a40514203e08190a7b067d8785076d7 completed June 27, 2026, 10:40 p.m.
NEDg Description generation batch_6a4051f3e8d08190b2e0db9d03b3a57e completed June 27, 2026, 10:43 p.m.
NED2 Entity disambiguation (via description) batch_6a4052c19cdc8190afb2e5e3f9374eaa completed June 27, 2026, 10:46 p.m.
Created at: May 3, 2026, 4:16 p.m.