Triple

T5785074
Position Surface form Disambiguated ID Type / Status
Subject Canaima airstrip E128249 entity
Predicate hasICAOCode P419 FINISHED
Object SVCN
SVCN is the ICAO airport code for Canaima airstrip, a small airport serving the Canaima National Park region in Venezuela.
 E547849 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: SVCN | Statement: [Canaima airstrip, hasICAOCode, SVCN]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: SVCN
Context triple: [Canaima airstrip, hasICAOCode, SVCN]
  • A. SVC
    SVC is scikit-learn’s implementation of a Support Vector Machine classifier used for supervised learning tasks such as binary and multiclass classification.
  • B. HVN
    HVN is the ICAO airline designator used to identify Vietnam Airlines in international aviation operations.
  • C. HVN
    HVN is the IATA airport code for Tweed New Haven Airport, a regional airport serving New Haven, Connecticut.
  • D. CNCS
    CNCS is the abbreviation for the Corporation for National and Community Service, the U.S. federal agency that supports national service programs like AmeriCorps and Senior Corps.
  • E. Novaliches
    Novaliches is a suburban district in northern Metro Manila, Philippines, known for its mixed residential and commercial areas and proximity to major water and nature reserves.
  • 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: SVCN
Triple: [Canaima airstrip, hasICAOCode, SVCN]
Generated description
SVCN is the ICAO airport code for Canaima airstrip, a small airport serving the Canaima National Park region in Venezuela.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: SVCN
Target entity description: SVCN is the ICAO airport code for Canaima airstrip, a small airport serving the Canaima National Park region in Venezuela.
  • A. SVC
    SVC is scikit-learn’s implementation of a Support Vector Machine classifier used for supervised learning tasks such as binary and multiclass classification.
  • B. HVN
    HVN is the ICAO airline designator used to identify Vietnam Airlines in international aviation operations.
  • C. HVN
    HVN is the IATA airport code for Tweed New Haven Airport, a regional airport serving New Haven, Connecticut.
  • D. CNCS
    CNCS is the abbreviation for the Corporation for National and Community Service, the U.S. federal agency that supports national service programs like AmeriCorps and Senior Corps.
  • E. Novaliches
    Novaliches is a suburban district in northern Metro Manila, Philippines, known for its mixed residential and commercial areas and proximity to major water and nature reserves.
  • 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_69c0084450048190bc647b649a05136b completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c02a1af0ec8190a47be1b7e7b5cda7 completed March 22, 2026, 5:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69c09815e5c08190a01ffad813e9d195 completed March 23, 2026, 1:32 a.m.
NEDg Description generation batch_69c0995672f08190acce2a14266ccf6a completed March 23, 2026, 1:37 a.m.
NED2 Entity disambiguation (via description) batch_69c099fefd6c8190ae1b4480ef133f02 completed March 23, 2026, 1:40 a.m.
Created at: March 22, 2026, 3:51 p.m.