Triple

T31003869
Position Surface form Disambiguated ID Type / Status
Subject Autair International Airways E790011 entity
Predicate predecessorOf P97 FINISHED
Object Court Line
Court Line was a British charter airline of the 1960s and 1970s known for its brightly colored aircraft and package holiday operations before its collapse in 1974.
E1941681 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: Court Line | Statement: [Autair International Airways, predecessorOf, Court Line]
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: Court Line
Triple: [Autair International Airways, predecessorOf, Court Line]
Generated description
Court Line was a British charter airline of the 1960s and 1970s known for its brightly colored aircraft and package holiday operations before its collapse in 1974.

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_69f224c73ca48190a1e46cb58ad4045b completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f6944331808190a5c5b3b30c8d3a7e completed May 3, 2026, 12:18 a.m.
NED1 Entity disambiguation (via context triple) batch_6a28fbd392cc81909ffad17b68be32a9 completed June 10, 2026, 5:53 a.m.
NEDg Description generation batch_6a2900ee287081908f719d29b7c73693 completed June 10, 2026, 6:15 a.m.
NED2 Entity disambiguation (via description) batch_6a2901f28f9c81909d9f04841e5f7fa5 completed June 10, 2026, 6:19 a.m.
Created at: April 29, 2026, 8:57 p.m.