Triple

T5220988
Position Surface form Disambiguated ID Type / Status
Subject Marina di Campo Airport E117866 entity
Predicate IATAcode P418 FINISHED
Object EBA
EBA is the IATA airport code for Marina di Campo Airport, which serves Italy’s Elba Island in the Tyrrhenian Sea.
 E504132 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: EBA | Statement: [Marina di Campo Airport, IATAcode, EBA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: EBA
Context triple: [Marina di Campo Airport, IATAcode, EBA]
  • A. EBA
    EBA is the European Union’s regulatory agency responsible for overseeing and harmonizing banking supervision and ensuring financial stability across member states.
  • B. ENBA
    ENBA is the commonly used abbreviation for the Escola Nacional de Belas Artes, a prominent national fine arts school.
  • C. EABIC
    EABIC is the acronym for the Ethiopian African Black International Congress, a prominent mansion within the Rastafari movement known for its Afrocentric theology and advocacy for Black liberation.
  • D. EBB
    EBB is the common abbreviation for Eisbären Berlin, a professional ice hockey team based in Berlin, Germany.
  • E. ENSBA
    ENSBA is the commonly used abbreviation for the École des Beaux-Arts, a prestigious French fine arts school renowned for its influence on art and architecture.
  • 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: EBA
Triple: [Marina di Campo Airport, IATAcode, EBA]
Generated description
EBA is the IATA airport code for Marina di Campo Airport, which serves Italy’s Elba Island in the Tyrrhenian Sea.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: EBA
Target entity description: EBA is the IATA airport code for Marina di Campo Airport, which serves Italy’s Elba Island in the Tyrrhenian Sea.
  • A. EBA
    EBA is the European Union’s regulatory agency responsible for overseeing and harmonizing banking supervision and ensuring financial stability across member states.
  • B. ENBA
    ENBA is the commonly used abbreviation for the Escola Nacional de Belas Artes, a prominent national fine arts school.
  • C. EABIC
    EABIC is the acronym for the Ethiopian African Black International Congress, a prominent mansion within the Rastafari movement known for its Afrocentric theology and advocacy for Black liberation.
  • D. EBB
    EBB is the common abbreviation for Eisbären Berlin, a professional ice hockey team based in Berlin, Germany.
  • E. ENSBA
    ENSBA is the commonly used abbreviation for the École des Beaux-Arts, a prestigious French fine arts school renowned for its influence on art and architecture.
  • 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_69bd4465e03081909bfcfd7113062590 completed March 20, 2026, 12:58 p.m.
NER Named-entity recognition batch_69bd7ab846548190bcd2c5cd238f6cd9 completed March 20, 2026, 4:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69beeff49d708190a042dfab473a9646 completed March 21, 2026, 7:22 p.m.
NEDg Description generation batch_69bef309c230819094ed6ae3fefe6e5b completed March 21, 2026, 7:35 p.m.
NED2 Entity disambiguation (via description) batch_69bef36c88f4819082931dbe1bb13f89 completed March 21, 2026, 7:37 p.m.
Created at: March 20, 2026, 1:48 p.m.