Triple

T14717792
Position Surface form Disambiguated ID Type / Status
Subject ASFA Yennenga E345728 entity
Predicate alsoKnownAs P39 FINISHED
Object ASFA-Y
ASFA-Y is an educational institution named after Princess Yennenga, often associated with secondary or technical schooling in Burkina Faso.
 E1116333 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: ASFA-Y | Statement: [ASFA Yennenga, alsoKnownAs, ASFA-Y]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: ASFA-Y
Context triple: [ASFA Yennenga, alsoKnownAs, ASFA-Y]
  • A. ASFA
    ASFA is a Spanish railway automatic train protection system designed to monitor and control train speeds to enhance operational safety.
  • B. AFS
    AFS is the National Rail station code for Ashford (Surrey) railway station in England.
  • C. AFSJ
    AFSJ is the European Union’s policy framework that governs cooperation on justice, security, border control, and fundamental rights across member states.
  • D. AsF
    AsF is the women’s organization within Germany’s Social Democratic Party (SPD) that advocates for gender equality and women’s rights in politics and society.
  • E. AFAS
    AFAS is a regional agreement among ASEAN member states aimed at progressively liberalizing trade in services to enhance economic integration and competitiveness in Southeast Asia.
  • 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: ASFA-Y
Triple: [ASFA Yennenga, alsoKnownAs, ASFA-Y]
Generated description
ASFA-Y is an educational institution named after Princess Yennenga, often associated with secondary or technical schooling in Burkina Faso.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: ASFA-Y
Target entity description: ASFA-Y is an educational institution named after Princess Yennenga, often associated with secondary or technical schooling in Burkina Faso.
  • A. ASFA
    ASFA is a Spanish railway automatic train protection system designed to monitor and control train speeds to enhance operational safety.
  • B. AFS
    AFS is the National Rail station code for Ashford (Surrey) railway station in England.
  • C. AFSJ
    AFSJ is the European Union’s policy framework that governs cooperation on justice, security, border control, and fundamental rights across member states.
  • D. AsF
    AsF is the women’s organization within Germany’s Social Democratic Party (SPD) that advocates for gender equality and women’s rights in politics and society.
  • E. AFAS
    AFAS is a regional agreement among ASEAN member states aimed at progressively liberalizing trade in services to enhance economic integration and competitiveness in Southeast Asia.
  • 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_69d822e5911c8190ba589f957dbd9ba7 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb98688f48190b2b19ce7aa06a6db completed April 14, 2026, 10:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69fdf0935f088190b54f2e106532972a completed May 8, 2026, 2:17 p.m.
NEDg Description generation batch_69fdf2a63cc88190b3670378c54c96b6 completed May 8, 2026, 2:26 p.m.
NED2 Entity disambiguation (via description) batch_69fdf31fcb4081908a88cf4d4c5ddced completed May 8, 2026, 2:28 p.m.
Created at: April 10, 2026, 1:29 a.m.