Triple

T2536931
Position Surface form Disambiguated ID Type / Status
Subject Regional Service Centre Entebbe E56290 entity
Predicate hasAbbreviation P43 FINISHED
Object RSCE
RSCE is a United Nations regional administrative and support hub based in Entebbe, Uganda, that provides shared services to UN missions and offices in Africa.
 E274073 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: RSCE | Statement: [Regional Service Centre Entebbe, hasAbbreviation, RSCE]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: RSCE
Context triple: [Regional Service Centre Entebbe, hasAbbreviation, RSCE]
  • A. SCSE
    SCSE is the ICAO airport code assigned to La Florida Airport in Chile.
  • B. RSC
    RSC is the commonly used abbreviation for the Royal Society of Canada, the national academy dedicated to promoting scholarly, scientific, and artistic excellence in Canada.
  • C. RSE
    RSE is the commonly used abbreviation for the Royal Society of Edinburgh, Scotland’s national academy of science and letters.
  • D. SRES
    SRES is the School of Resources and Environmental Science at Wuhan University, a faculty focused on education and research in natural resources, geography, and environmental science.
  • E. ESC
    ESC is the abbreviated name of the Energy Systems Committee, a group focused on issues related to energy systems.
  • 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: RSCE
Triple: [Regional Service Centre Entebbe, hasAbbreviation, RSCE]
Generated description
RSCE is a United Nations regional administrative and support hub based in Entebbe, Uganda, that provides shared services to UN missions and offices in Africa.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: RSCE
Target entity description: RSCE is a United Nations regional administrative and support hub based in Entebbe, Uganda, that provides shared services to UN missions and offices in Africa.
  • A. SCSE
    SCSE is the ICAO airport code assigned to La Florida Airport in Chile.
  • B. RSC
    RSC is the commonly used abbreviation for the Royal Society of Canada, the national academy dedicated to promoting scholarly, scientific, and artistic excellence in Canada.
  • C. RSE
    RSE is the commonly used abbreviation for the Royal Society of Edinburgh, Scotland’s national academy of science and letters.
  • D. SRES
    SRES is the School of Resources and Environmental Science at Wuhan University, a faculty focused on education and research in natural resources, geography, and environmental science.
  • E. ESC
    ESC is the abbreviated name of the Energy Systems Committee, a group focused on issues related to energy systems.
  • 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_69ab4a49b6508190bc467fbef4bac334 completed March 6, 2026, 9:42 p.m.
NER Named-entity recognition batch_69abd297e9a881909e592187a78eacaa completed March 7, 2026, 7:24 a.m.
NED1 Entity disambiguation (via context triple) batch_69af2bbf248481908f588bc1cf46d168 completed March 9, 2026, 8:21 p.m.
NEDg Description generation batch_69af43444ba481909311e86f5ab3a2c9 completed March 9, 2026, 10:01 p.m.
NED2 Entity disambiguation (via description) batch_69af43a2055c8190906a984afe0298c9 completed March 9, 2026, 10:03 p.m.
Created at: March 6, 2026, 9:47 p.m.