Triple

T3173926
Position Surface form Disambiguated ID Type / Status
Subject Fannie Mae E66416 entity
Predicate formerTickerSymbol P23749 FINISHED
Object FNM
FNM was the former stock ticker symbol for Fannie Mae, the U.S. government-sponsored enterprise that provides liquidity and stability to the mortgage market.
 E333112 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: FNM | Statement: [Fannie Mae, formerTickerSymbol, FNM]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: FNM
Context triple: [Fannie Mae, formerTickerSymbol, FNM]
  • A. FNC
    FNC is the IATA airport code for Cristiano Ronaldo Madeira International Airport, the main air gateway to Portugal’s Madeira Island.
  • B. FNS
    FNS is the U.S. Department of Agriculture agency that administers federal food assistance and nutrition programs such as SNAP and school meals.
  • C. HNM
    HNM is the IATA airport code for Hana Airport, a small regional airport serving the town of Hana on the island of Maui in Hawaii.
  • D. FMG
    FMG is the Faculty of Social and Behavioural Sciences at the University of Amsterdam, encompassing disciplines such as psychology, sociology, political science, and communication science.
  • E. FED
    FED is the commonly used abbreviation for the Fluids Engineering Division, a professional group focused on research and advancements in fluid mechanics and related technologies.
  • 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: FNM
Triple: [Fannie Mae, formerTickerSymbol, FNM]
Generated description
FNM was the former stock ticker symbol for Fannie Mae, the U.S. government-sponsored enterprise that provides liquidity and stability to the mortgage market.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: FNM
Target entity description: FNM was the former stock ticker symbol for Fannie Mae, the U.S. government-sponsored enterprise that provides liquidity and stability to the mortgage market.
  • A. FNC
    FNC is the IATA airport code for Cristiano Ronaldo Madeira International Airport, the main air gateway to Portugal’s Madeira Island.
  • B. FNS
    FNS is the U.S. Department of Agriculture agency that administers federal food assistance and nutrition programs such as SNAP and school meals.
  • C. HNM
    HNM is the IATA airport code for Hana Airport, a small regional airport serving the town of Hana on the island of Maui in Hawaii.
  • D. FMG
    FMG is the Faculty of Social and Behavioural Sciences at the University of Amsterdam, encompassing disciplines such as psychology, sociology, political science, and communication science.
  • E. FED
    FED is the commonly used abbreviation for the Fluids Engineering Division, a professional group focused on research and advancements in fluid mechanics and related technologies.
  • 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_69ad8586a34c8190944c63ec11a8de1a completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69ada670c800819098937783e2b05c7a completed March 8, 2026, 4:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69b235edf7708190b79605a05baf1711 completed March 12, 2026, 3:41 a.m.
NEDg Description generation batch_69b236e61ae88190a76b942c6cddff41 completed March 12, 2026, 3:45 a.m.
NED2 Entity disambiguation (via description) batch_69b23770ed4c8190b5d929cc95a286a0 completed March 12, 2026, 3:48 a.m.
Created at: March 8, 2026, 3:06 p.m.