Triple

T8431123
Position Surface form Disambiguated ID Type / Status
Subject ARRAY E199115 entity
Predicate shortName P43 FINISHED
Object AFFRM
AFFRM (African-American Film Festival Releasing Movement) was a distribution collective dedicated to releasing and promoting independent films by and about Black people in the United States.
E732707 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: AFFRM | Statement: [ARRAY, shortName, AFFRM]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: AFFRM
Context triple: [ARRAY, shortName, AFFRM]
  • A. AFF
    AFF is the ASEAN Football Federation, the regional governing body for football in Southeast Asia under the Asian Football Confederation.
  • B. AFRM
    AFRM is the stock ticker symbol for Affirm Holdings, Inc., a financial technology company known for its buy-now-pay-later payment solutions.
  • C. 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.
  • D. AAF
    AAF is the common abbreviation for the Alliance of American Football, a short-lived professional American football league that operated in 2019.
  • E. AF
    AF is a 16-bit register pair in the Zilog Z80 CPU that combines the accumulator (A) and the flags register (F) for arithmetic and logic operations.
  • 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: AFFRM
Triple: [ARRAY, shortName, AFFRM]
Generated description
AFFRM (African-American Film Festival Releasing Movement) was a distribution collective dedicated to releasing and promoting independent films by and about Black people in the United States.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: AFFRM
Target entity description: AFFRM (African-American Film Festival Releasing Movement) was a distribution collective dedicated to releasing and promoting independent films by and about Black people in the United States.
  • A. AFF
    AFF is the ASEAN Football Federation, the regional governing body for football in Southeast Asia under the Asian Football Confederation.
  • B. AFRM
    AFRM is the stock ticker symbol for Affirm Holdings, Inc., a financial technology company known for its buy-now-pay-later payment solutions.
  • C. 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.
  • D. AAF
    AAF is the common abbreviation for the Alliance of American Football, a short-lived professional American football league that operated in 2019.
  • 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_69ca8313c99081909a5c6d83b91de5b3 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbd1a4876c81908d5a708bb1f35683 completed March 31, 2026, 1:52 p.m.
NED1 Entity disambiguation (via context triple) batch_69ce0380ed948190bdba247d67769ade completed April 2, 2026, 5:49 a.m.
NEDg Description generation batch_69ce07851c4081909a9468a386035bb2 completed April 2, 2026, 6:07 a.m.
NED2 Entity disambiguation (via description) batch_69ce07ec00248190bb10fee54265c7f9 completed April 2, 2026, 6:08 a.m.
Created at: March 30, 2026, 6:07 p.m.