Triple

T5972583
Position Surface form Disambiguated ID Type / Status
Subject Federation of European Securities Exchanges E132909 entity
Predicate abbreviation P43 FINISHED
Object FESE
FESE is the main industry association representing European securities exchanges and other market operators at the European and global level.
 E559743 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: FESE | Statement: [Federation of European Securities Exchanges, abbreviation, FESE]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: FESE
Context triple: [Federation of European Securities Exchanges, abbreviation, FESE]
  • A. FAES
    FAES is the acronym for the Armed Forces of El Salvador, the country's unified military institution responsible for national defense and security.
  • B. FSE
    FSE is the Faculty of Science and Engineering at the University of Groningen, encompassing a broad range of natural sciences, engineering, and technology disciplines.
  • C. FSE
    FSE (Fast Software Encryption) is a leading international research conference focused on the design and analysis of symmetric-key cryptographic primitives and algorithms.
  • D. FSE
    FSE is a premier international research conference on software engineering organized under ACM SIGSOFT.
  • E. FEAS
    FEAS is the Faculty of Engineering and Architectural Science at Toronto Metropolitan University, encompassing programs in engineering, architecture, and related applied sciences.
  • 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: FESE
Triple: [Federation of European Securities Exchanges, abbreviation, FESE]
Generated description
FESE is the main industry association representing European securities exchanges and other market operators at the European and global level.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: FESE
Target entity description: FESE is the main industry association representing European securities exchanges and other market operators at the European and global level.
  • A. FAES
    FAES is the acronym for the Armed Forces of El Salvador, the country's unified military institution responsible for national defense and security.
  • B. FSE
    FSE is the Faculty of Science and Engineering at the University of Groningen, encompassing a broad range of natural sciences, engineering, and technology disciplines.
  • C. FSE
    FSE (Fast Software Encryption) is a leading international research conference focused on the design and analysis of symmetric-key cryptographic primitives and algorithms.
  • D. FSE
    FSE is a premier international research conference on software engineering organized under ACM SIGSOFT.
  • E. FEAS
    FEAS is the Faculty of Engineering and Architectural Science at Toronto Metropolitan University, encompassing programs in engineering, architecture, and related applied sciences.
  • 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_69c0086deab081908550159ca23eec9b completed March 22, 2026, 3:19 p.m.
NER Named-entity recognition batch_69c04a00c3588190b335d7d3341b6d68 completed March 22, 2026, 7:58 p.m.
NED1 Entity disambiguation (via context triple) batch_69c0e40fa2488190b82d604d51b73090 completed March 23, 2026, 6:56 a.m.
NEDg Description generation batch_69c0f85e33d8819080d9d721421b4c5b completed March 23, 2026, 8:22 a.m.
NED2 Entity disambiguation (via description) batch_69c0fad0bdf08190bf6599d492848582 completed March 23, 2026, 8:33 a.m.
Created at: March 22, 2026, 4:03 p.m.