Triple

T13087158
Position Surface form Disambiguated ID Type / Status
Subject Inter&Co Stadium E310365 entity
Predicate sponsor P67 FINISHED
Object Inter&Co
Inter&Co is a Brazilian digital financial services company known for offering banking, investment, and insurance products through a unified online platform.
E1021160 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: Inter&Co | Statement: [Inter&Co Stadium, sponsor, Inter&Co]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Inter&Co
Context triple: [Inter&Co Stadium, sponsor, Inter&Co]
  • A. M&Co
    M&Co was a pioneering New York–based graphic design firm founded by Tibor Kalman, renowned for its influential, concept-driven work in branding, editorial, and album cover design.
  • B. Denis of Paris
    Denis of Paris is a 3rd-century Christian martyr and bishop, venerated as the patron saint of Paris and traditionally regarded as one of the city’s earliest evangelizers.
  • C. La Senza
    La Senza is a Canadian-based lingerie and intimate apparel retailer known for its affordable, fashion-focused underwear and sleepwear collections.
  • D. Marchesa
    Marchesa is the Italian noble title traditionally used to designate a woman holding the rank of marquess.
  • E. Marchesa
    Marchesa is a luxury fashion label renowned for its ornate, red-carpet-ready eveningwear and bridal gowns.
  • 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: Inter&Co
Triple: [Inter&Co Stadium, sponsor, Inter&Co]
Generated description
Inter&Co is a Brazilian digital financial services company known for offering banking, investment, and insurance products through a unified online platform.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Inter&Co
Target entity description: Inter&Co is a Brazilian digital financial services company known for offering banking, investment, and insurance products through a unified online platform.
  • A. M&Co
    M&Co was a pioneering New York–based graphic design firm founded by Tibor Kalman, renowned for its influential, concept-driven work in branding, editorial, and album cover design.
  • B. Denis of Paris
    Denis of Paris is a 3rd-century Christian martyr and bishop, venerated as the patron saint of Paris and traditionally regarded as one of the city’s earliest evangelizers.
  • C. La Senza
    La Senza is a Canadian-based lingerie and intimate apparel retailer known for its affordable, fashion-focused underwear and sleepwear collections.
  • D. Marchesa
    Marchesa is the Italian noble title traditionally used to designate a woman holding the rank of marquess.
  • E. Marchesa
    Marchesa is a luxury fashion label renowned for its ornate, red-carpet-ready eveningwear and bridal gowns.
  • 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_69d806a733548190989cfd4ce981ca33 completed April 9, 2026, 8:05 p.m.
NER Named-entity recognition batch_69d981378dd08190b4f00e4e5df0e480 completed April 10, 2026, 11:01 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6d61060188190911eb3e135dc25ac completed May 3, 2026, 4:58 a.m.
NEDg Description generation batch_69f6dae595908190b27980e48514cda5 completed May 3, 2026, 5:19 a.m.
NED2 Entity disambiguation (via description) batch_69f6db8f68a4819091d8e67d9c8eec81 completed May 3, 2026, 5:22 a.m.
Created at: April 9, 2026, 9:02 p.m.