Triple

T23368253
Position Surface form Disambiguated ID Type / Status
Subject University of Yaoundé II E593384 entity
Predicate campus P269 FINISHED
Object Soa
Soa is a town in Cameroon known for hosting the main campus of the University of Yaoundé II.
 E1582736 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: Soa | Statement: [University of Yaoundé II, campus, Soa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Soa
Context triple: [University of Yaoundé II, campus, Soa]
  • A. SOA
    SOA is the three-letter National Rail station code for Southampton Airport Parkway railway station in Hampshire, England.
  • B. SOA
    SOA is the abbreviation commonly used for the School of the Americas, a controversial U.S. military training institution for Latin American soldiers.
  • C. SOA
    SOA is the abbreviation for China’s State Oceanic Administration, the government agency formerly responsible for managing the country’s maritime affairs and oceanic resources.
  • D. SOAF
    SOAF is the commonly used abbreviation for the Sultan of Oman's Armed Forces, the unified military organization responsible for defending the Sultanate of Oman.
  • E. ASOEA
    ASOEA is the acronym for the Air and Space Organizational Excellence Award, a U.S. military honor recognizing outstanding performance by Air and Space Force units.
  • 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: Soa
Triple: [University of Yaoundé II, campus, Soa]
Generated description
Soa is a town in Cameroon known for hosting the main campus of the University of Yaoundé II.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Soa
Target entity description: Soa is a town in Cameroon known for hosting the main campus of the University of Yaoundé II.
  • A. SOA
    SOA is the three-letter National Rail station code for Southampton Airport Parkway railway station in Hampshire, England.
  • B. SOA
    SOA is the abbreviation commonly used for the School of the Americas, a controversial U.S. military training institution for Latin American soldiers.
  • C. SOA
    SOA is the abbreviation for China’s State Oceanic Administration, the government agency formerly responsible for managing the country’s maritime affairs and oceanic resources.
  • D. SOAF
    SOAF is the commonly used abbreviation for the Sultan of Oman's Armed Forces, the unified military organization responsible for defending the Sultanate of Oman.
  • E. ASOEA
    ASOEA is the acronym for the Air and Space Organizational Excellence Award, a U.S. military honor recognizing outstanding performance by Air and Space Force units.
  • 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_69e25d2593c88190bcdf4a716a94ccb2 completed April 17, 2026, 4:17 p.m.
NER Named-entity recognition batch_69f1a0aed374819097d38f51894bee44 completed April 29, 2026, 6:09 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0c5ddbd8688190ba51358f22b8fb43 completed May 19, 2026, 12:55 p.m.
NEDg Description generation batch_6a0c5f90146c8190b5035747abcfdb6e completed May 19, 2026, 1:03 p.m.
NED2 Entity disambiguation (via description) batch_6a0c601b5d288190b5cf4f3e0c8cde15 completed May 19, 2026, 1:05 p.m.
Created at: April 17, 2026, 5:32 p.m.