Triple

T8017921
Position Surface form Disambiguated ID Type / Status
Subject Göppingen station E186665 entity
Predicate hasStationCode P1289 FINISHED
Object IGOE
IGOE is the railway station code used to identify Göppingen station in Germany’s rail network.
 E707660 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: IGOE | Statement: [Göppingen station, hasStationCode, IGOE]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: IGOE
Context triple: [Göppingen station, hasStationCode, IGOE]
  • A. IGU
    IGU is the IATA airport code for Foz do Iguaçu International Airport in Brazil, serving the Iguaçu Falls region.
  • B. IGR
    IGR is the IATA airport code for Cataratas del Iguazú International Airport serving Puerto Iguazú in Argentina, a gateway to the Iguazú Falls.
  • C. ISAGO
    ISAGO is the International Air Transport Association’s global safety audit program for ground service providers, aimed at improving operational safety and standardizing ground handling practices in aviation.
  • D. IOE
    IOE is the University College London Institute of Education, a leading centre for research and teaching in education and social science.
  • E. IOE
    IOE is the Independent Office of Evaluation of the International Fund for Agricultural Development, responsible for assessing the effectiveness and impact of IFAD’s strategies and operations.
  • 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: IGOE
Triple: [Göppingen station, hasStationCode, IGOE]
Generated description
IGOE is the railway station code used to identify Göppingen station in Germany’s rail network.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: IGOE
Target entity description: IGOE is the railway station code used to identify Göppingen station in Germany’s rail network.
  • A. IGU
    IGU is the IATA airport code for Foz do Iguaçu International Airport in Brazil, serving the Iguaçu Falls region.
  • B. IGR
    IGR is the IATA airport code for Cataratas del Iguazú International Airport serving Puerto Iguazú in Argentina, a gateway to the Iguazú Falls.
  • C. ISAGO
    ISAGO is the International Air Transport Association’s global safety audit program for ground service providers, aimed at improving operational safety and standardizing ground handling practices in aviation.
  • D. IOE
    IOE is the University College London Institute of Education, a leading centre for research and teaching in education and social science.
  • E. IOE
    IOE is the Independent Office of Evaluation of the International Fund for Agricultural Development, responsible for assessing the effectiveness and impact of IFAD’s strategies and operations.
  • 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_69ca82ac7fc081909b1398cf025423af completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb3df4f1b8819089a8b67f136bce9a completed March 31, 2026, 3:22 a.m.
NED1 Entity disambiguation (via context triple) batch_69cc56c213ec8190b3bd96c42d1357e4 completed March 31, 2026, 11:20 p.m.
NEDg Description generation batch_69cc58a9e94081908980e2c60be38642 completed March 31, 2026, 11:28 p.m.
NED2 Entity disambiguation (via description) batch_69cc5cbaefb481909eb325f0d27675c0 completed March 31, 2026, 11:46 p.m.
Created at: March 30, 2026, 5:20 p.m.