Triple

T12324707
Position Surface form Disambiguated ID Type / Status
Subject Faculty of Economic Sciences E293798 entity
Predicate shortName P43 FINISHED
Object FES
FES is the abbreviated name commonly used for the Faculty of Economic Sciences, an academic institution focused on economics and related disciplines.
 E975136 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: FES | Statement: [Faculty of Economic Sciences, shortName, FES]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: FES
Context triple: [Faculty of Economic Sciences, shortName, FES]
  • 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. FIES
    FIES is a globally used survey-based metric developed by the FAO to assess the severity and prevalence of food insecurity at the individual or household level.
  • C. FEF
    FEF is the commonly used abbreviation for the Ecuadorian Football Federation, the governing body of football in Ecuador.
  • D. FSP
    FSP is the station code used to identify Schweizer Platz station in the Frankfurt public transport network.
  • E. FÜS
    FÜS is the vehicle registration code for the town of Füssen in the Ostallgäu district of Bavaria, Germany.
  • 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: FES
Triple: [Faculty of Economic Sciences, shortName, FES]
Generated description
FES is the abbreviated name commonly used for the Faculty of Economic Sciences, an academic institution focused on economics and related disciplines.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: FES
Target entity description: FES is the abbreviated name commonly used for the Faculty of Economic Sciences, an academic institution focused on economics and related disciplines.
  • 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. FIES
    FIES is a globally used survey-based metric developed by the FAO to assess the severity and prevalence of food insecurity at the individual or household level.
  • C. FEF
    FEF is the commonly used abbreviation for the Ecuadorian Football Federation, the governing body of football in Ecuador.
  • D. FSP
    FSP is the station code used to identify Schweizer Platz station in the Frankfurt public transport network.
  • E. FÜS
    FÜS is the vehicle registration code for the town of Füssen in the Ostallgäu district of Bavaria, Germany.
  • 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_69d6ab6ae0dc8190b1522a9c1c55c114 completed April 8, 2026, 7:24 p.m.
NER Named-entity recognition batch_69d93f4e7e588190b37e2413bc649198 completed April 10, 2026, 6:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69f61e8d27288190bdf32acd600141db completed May 2, 2026, 3:55 p.m.
NEDg Description generation batch_69f61f9493d081909a543bcafeb508d1 completed May 2, 2026, 4 p.m.
NED2 Entity disambiguation (via description) batch_69f620ad9ec0819099909142fbad6412 completed May 2, 2026, 4:05 p.m.
Created at: April 8, 2026, 9:53 p.m.