Triple

T29908156
Position Surface form Disambiguated ID Type / Status
Subject TAM E759594 entity
Predicate formerFrequentFlyerProgram P13481 FINISHED
Object TAM Fidelidade
TAM Fidelidade was the frequent-flyer loyalty program of Brazilian airline TAM, allowing passengers to earn and redeem miles for flights and related benefits.
 E1889859 NE FINISHED

How this triple was built (3 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: TAM Fidelidade | Statement: [TAM, formerFrequentFlyerProgram, TAM Fidelidade]
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: TAM Fidelidade
Triple: [TAM, formerFrequentFlyerProgram, TAM Fidelidade]
Generated description
TAM Fidelidade was the frequent-flyer loyalty program of Brazilian airline TAM, allowing passengers to earn and redeem miles for flights and related benefits.
PD Predicate disambiguation gpt-5-mini-2025-08-07 
Target predicate: formerFrequentFlyerProgram
Context triple: [TAM, formerFrequentFlyerProgram, TAM Fidelidade]
  • A. associatedWithFrequentFlyerProgram chosen
    Indicates that an entity has a connection or involvement with a frequent flyer program, such as membership, participation, or affiliation.
  • B. formerIATAcode
    Indicates that an entity previously held a specific IATA code, which is no longer its current assigned code.
  • C. formerLoyalty
    Indicates that an entity previously had a loyalty or allegiance to another entity, but no longer does.
  • D. airlineFormerName
    Indicates that an airline previously operated under a different name, specifying its former official designation.
  • E. successorAirline
    Indicates that one airline has taken over, replaced, or continued the operations of another airline as its successor.
  • F. None of above.

Provenance (6 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_69f224600590819085e148a01c056ef6 completed April 29, 2026, 3:31 p.m.
NER Named-entity recognition batch_69febce5877c8190a5e000ef5331ec88 completed May 9, 2026, 4:49 a.m.
NED1 Entity disambiguation (via context triple) batch_6a26f1ee56f48190a047a86b00096e3d completed June 8, 2026, 4:46 p.m.
NEDg Description generation batch_6a26f35e46b08190b5f66716be384ca9 completed June 8, 2026, 4:52 p.m.
NED2 Entity disambiguation (via description) batch_6a26f46b6b048190ae3168913b1b1ce8 completed June 8, 2026, 4:57 p.m.
PD Predicate disambiguation batch_69febad1cd588190abc7686bcb39a371 completed May 9, 2026, 4:40 a.m.
Created at: April 29, 2026, 6:09 p.m.