Triple

T2906212
Position Surface form Disambiguated ID Type / Status
Subject Convention Center Station E62769 entity
Predicate hasStationCode P1289 FINISHED
Object CONV
CONV is the station code for Convention Center Station, a public transit stop typically serving a nearby convention or exhibition center.
 E310343 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: CONV | Statement: [Convention Center Station, hasStationCode, CONV]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: CONV
Context triple: [Convention Center Station, hasStationCode, CONV]
  • A. CONVEL
    CONVEL is a train control and safety system used on Portugal’s high-speed Alfa Pendular services to monitor and protect train operations.
  • B. CONSOB
    CONSOB is Italy’s national securities and financial markets regulator, overseeing the transparency and proper functioning of the country’s stock exchanges and investment services.
  • C. COR
    COR is the IATA airport code for Ingeniero Aeronáutico Ambrosio L.V. Taravella International Airport serving Córdoba, Argentina.
  • D. Coll
    Coll is a small, sparsely populated island in the Inner Hebrides of Scotland, known for its sandy beaches, dark skies, and rich wildlife.
  • E. ENC
    ENC is an FTP security extension command that provides data confidentiality by encrypting the contents of file transfers.
  • 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: CONV
Triple: [Convention Center Station, hasStationCode, CONV]
Generated description
CONV is the station code for Convention Center Station, a public transit stop typically serving a nearby convention or exhibition center.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: CONV
Target entity description: CONV is the station code for Convention Center Station, a public transit stop typically serving a nearby convention or exhibition center.
  • A. CONVEL
    CONVEL is a train control and safety system used on Portugal’s high-speed Alfa Pendular services to monitor and protect train operations.
  • B. CONSOB
    CONSOB is Italy’s national securities and financial markets regulator, overseeing the transparency and proper functioning of the country’s stock exchanges and investment services.
  • C. COR
    COR is the IATA airport code for Ingeniero Aeronáutico Ambrosio L.V. Taravella International Airport serving Córdoba, Argentina.
  • D. Coll
    Coll is a small, sparsely populated island in the Inner Hebrides of Scotland, known for its sandy beaches, dark skies, and rich wildlife.
  • E. ENC
    ENC is an FTP security extension command that provides data confidentiality by encrypting the contents of file transfers.
  • 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_69ab4c3e070c8190b78d3d2c005876dd completed March 6, 2026, 9:50 p.m.
NER Named-entity recognition batch_69abe0cee7988190875665145c3cd605 completed March 7, 2026, 8:24 a.m.
NED1 Entity disambiguation (via context triple) batch_69b05612e79081908c962c2fe2e362d6 completed March 10, 2026, 5:34 p.m.
NEDg Description generation batch_69b0622ea7b081908fe2029e61e21766 completed March 10, 2026, 6:25 p.m.
NED2 Entity disambiguation (via description) batch_69b0630cd0348190882a4d3d90b217c3 completed March 10, 2026, 6:29 p.m.
Created at: March 6, 2026, 10:11 p.m.