Triple

T29946566
Position Surface form Disambiguated ID Type / Status
Subject LATAM Airlines Group E760646 entity
Predicate hasSubsidiary P254 FINISHED
Object LATAM Airlines Ecuador
LATAM Airlines Ecuador is an Ecuadorian airline operating domestic and international passenger flights as part of the larger LATAM Airlines Group network.
E1895350 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: LATAM Airlines Ecuador | Statement: [LATAM Airlines Group, hasSubsidiary, LATAM Airlines Ecuador]
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: LATAM Airlines Ecuador
Triple: [LATAM Airlines Group, hasSubsidiary, LATAM Airlines Ecuador]
Generated description
LATAM Airlines Ecuador is an Ecuadorian airline operating domestic and international passenger flights as part of the larger LATAM Airlines Group network.

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_69f2246562b881909d57622f4086d43d completed April 29, 2026, 3:31 p.m.
NER Named-entity recognition batch_69f6780c47b08190adbfa6f39c9be072 completed May 2, 2026, 10:17 p.m.
NED1 Entity disambiguation (via context triple) batch_6a2721ede0708190999bf4343f334508 completed June 8, 2026, 8:11 p.m.
NEDg Description generation batch_6a2722e635488190b4dd3cf0e212f790 completed June 8, 2026, 8:15 p.m.
NED2 Entity disambiguation (via description) batch_6a2727b3fa008190a3d9bb95a065af14 completed June 8, 2026, 8:36 p.m.
Created at: April 29, 2026, 6:24 p.m.