Triple

T15172114
Position Surface form Disambiguated ID Type / Status
Subject Międzyrzecz E362510 entity
Predicate hasCarPlatesCode P26915 FINISHED
Object FMI
FMI is the vehicle registration code assigned to the town of Międzyrzecz in western Poland.
 E1142587 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: FMI | Statement: [Międzyrzecz, hasCarPlatesCode, FMI]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: FMI
Context triple: [Międzyrzecz, hasCarPlatesCode, FMI]
  • A. FMU
    FMU is a public university in Florence, South Carolina, known for its liberal arts and professional programs.
  • B. FMA
    FMA is an acronym commonly used for Fault Management Architecture, a system framework for detecting, diagnosing, and resolving hardware and software faults in computing environments.
  • C. FNI
    FNI is the IATA airport code for Nîmes-Alès-Camargue-Cévennes Airport in southern France.
  • D. FBR
    FBR is Pakistan’s federal government agency responsible for tax collection, enforcement of fiscal laws, and formulation of revenue-related policies.
  • E. 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.
  • 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: FMI
Triple: [Międzyrzecz, hasCarPlatesCode, FMI]
Generated description
FMI is the vehicle registration code assigned to the town of Międzyrzecz in western Poland.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: FMI
Target entity description: FMI is the vehicle registration code assigned to the town of Międzyrzecz in western Poland.
  • A. FMU
    FMU is a public university in Florence, South Carolina, known for its liberal arts and professional programs.
  • B. FMA
    FMA is an acronym commonly used for Fault Management Architecture, a system framework for detecting, diagnosing, and resolving hardware and software faults in computing environments.
  • C. FNI
    FNI is the IATA airport code for Nîmes-Alès-Camargue-Cévennes Airport in southern France.
  • D. FBR
    FBR is Pakistan’s federal government agency responsible for tax collection, enforcement of fiscal laws, and formulation of revenue-related policies.
  • E. 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.
  • 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_69d85a087b7c81908baa94a53dac8d68 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e006501b488190a2ab09dbf1532571 completed April 15, 2026, 9:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69fec88c69088190a61f0a5719e99b87 completed May 9, 2026, 5:39 a.m.
NEDg Description generation batch_69fec93109c08190a3499e4520e31604 completed May 9, 2026, 5:42 a.m.
NED2 Entity disambiguation (via description) batch_69fecc6fa8f88190aa6956e6e2b1f8ab completed May 9, 2026, 5:55 a.m.
Created at: April 10, 2026, 3:09 a.m.