Triple

T6047106
Position Surface form Disambiguated ID Type / Status
Subject Affirm E134694 entity
Predicate tickerSymbol P1447 FINISHED
Object AFRM
AFRM is the stock ticker symbol for Affirm Holdings, Inc., a financial technology company known for its buy-now-pay-later payment solutions.
 E564973 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: AFRM | Statement: [Affirm, tickerSymbol, AFRM]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: AFRM
Context triple: [Affirm, tickerSymbol, AFRM]
  • A. AFRF
    AFRF is the commonly used English abbreviation for the Russian Armed Forces, the military organization responsible for the defense and security of the Russian Federation.
  • B. AFR
    AFR is the USAID Bureau for Africa, the division responsible for planning and managing U.S. development and humanitarian assistance programs across the African continent.
  • C. AFR
    AFR is the ICAO airline designator used to identify Air France flights in international aviation operations.
  • D. AF
    AF is the two-letter ISO 3166-1 alpha-2 country code assigned to Afghanistan for international standardization and referencing.
  • E. AF
    AF is the two-letter IATA airline designator assigned to Air France, the flag carrier of France.
  • 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: AFRM
Triple: [Affirm, tickerSymbol, AFRM]
Generated description
AFRM is the stock ticker symbol for Affirm Holdings, Inc., a financial technology company known for its buy-now-pay-later payment solutions.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: AFRM
Target entity description: AFRM is the stock ticker symbol for Affirm Holdings, Inc., a financial technology company known for its buy-now-pay-later payment solutions.
  • A. AFRF
    AFRF is the commonly used English abbreviation for the Russian Armed Forces, the military organization responsible for the defense and security of the Russian Federation.
  • B. AFR
    AFR is the USAID Bureau for Africa, the division responsible for planning and managing U.S. development and humanitarian assistance programs across the African continent.
  • C. AFR
    AFR is the ICAO airline designator used to identify Air France flights in international aviation operations.
  • D. AF
    AF is the two-letter ISO 3166-1 alpha-2 country code assigned to Afghanistan for international standardization and referencing.
  • E. AF
    AF is the two-letter IATA airline designator assigned to Air France, the flag carrier of France.
  • 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_69c00876a69881908088a2626d3b2666 completed March 22, 2026, 3:19 p.m.
NER Named-entity recognition batch_69c056e70fd48190b4554e9a516a1c88 completed March 22, 2026, 8:53 p.m.
NED1 Entity disambiguation (via context triple) batch_69c113a2b65c8190a1891e790cb9a5de completed March 23, 2026, 10:19 a.m.
NEDg Description generation batch_69c11551bec88190be77db3ec96045ad completed March 23, 2026, 10:26 a.m.
NED2 Entity disambiguation (via description) batch_69c115f88e948190a3ea11b33742779c completed March 23, 2026, 10:29 a.m.
Created at: March 22, 2026, 4:09 p.m.