Triple
T4155074
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | United Nations country teams in Central Africa |
E91396
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object |
United Nations country team in São Tomé and Príncipe
The United Nations country team in São Tomé and Príncipe is the collective group of UN agencies, funds, and programmes working together in the country to support its development priorities and the implementation of the UN’s global agenda.
|
E104020
|
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: United Nations country team in São Tomé and Príncipe | Statement: [United Nations country teams in Central Africa, hasPart, United Nations country team in São Tomé and Príncipe]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: United Nations country team in São Tomé and Príncipe Context triple: [United Nations country teams in Central Africa, hasPart, United Nations country team in São Tomé and Príncipe]
-
A.
United Nations country teams in Central Africa
United Nations country teams in Central Africa are integrated groups of UN agencies, funds, and programmes working together at the country level to support national development priorities, peacebuilding, and humanitarian efforts across the Central African subregion.
-
B.
UN Country Teams
UN Country Teams are in-country groups of UN agencies, funds, and programmes that coordinate their efforts to support national development priorities and the implementation of the UN’s work at the country level.
-
C.
UN country teams in West Africa
UN country teams in West Africa are integrated UN coordination bodies in each country that bring together UN agencies, funds, and programmes to support national development priorities, peacebuilding, and humanitarian efforts across the subregion.
-
D.
United Nations country teams in North Africa
United Nations country teams in North Africa are coordinated groups of UN agencies, funds, and programmes working together within each North African country to support national development priorities and the implementation of UN mandates.
-
E.
African Union Partnership Team
The African Union Partnership Team is a specialized unit within the UN Department of Peace Operations that focuses on coordinating and strengthening peace and security collaboration with the African Union.
- 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: United Nations country team in São Tomé and Príncipe Triple: [United Nations country teams in Central Africa, hasPart, United Nations country team in São Tomé and Príncipe]
Generated description
The United Nations country team in São Tomé and Príncipe is the collective group of UN agencies, funds, and programmes working together in the country to support its development priorities and the implementation of the UN’s global agenda.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: United Nations country team in São Tomé and Príncipe Target entity description: The United Nations country team in São Tomé and Príncipe is the collective group of UN agencies, funds, and programmes working together in the country to support its development priorities and the implementation of the UN’s global agenda.
-
A.
United Nations country teams in Central Africa
United Nations country teams in Central Africa are integrated groups of UN agencies, funds, and programmes working together at the country level to support national development priorities, peacebuilding, and humanitarian efforts across the Central African subregion.
-
B.
UN Country Teams
chosen
UN Country Teams are in-country groups of UN agencies, funds, and programmes that coordinate their efforts to support national development priorities and the implementation of the UN’s work at the country level.
-
C.
UN country teams in West Africa
UN country teams in West Africa are integrated UN coordination bodies in each country that bring together UN agencies, funds, and programmes to support national development priorities, peacebuilding, and humanitarian efforts across the subregion.
-
D.
United Nations country teams in North Africa
United Nations country teams in North Africa are coordinated groups of UN agencies, funds, and programmes working together within each North African country to support national development priorities and the implementation of UN mandates.
-
E.
African Union Partnership Team
The African Union Partnership Team is a specialized unit within the UN Department of Peace Operations that focuses on coordinating and strengthening peace and security collaboration with the African Union.
- F. None of above.
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_69aed9626ebc8190a39de631788bea3e |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69af028e3e5c8190bc1d5a9b9dff1d14 |
completed | March 9, 2026, 5:25 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b57f3c0d7c819098d67e012ef30818 |
completed | March 14, 2026, 3:31 p.m. |
| NEDg | Description generation | batch_69b580260a588190a2e1a84513a8c72f |
completed | March 14, 2026, 3:35 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b580c46e7481908aa13c6d7c6e36de |
completed | March 14, 2026, 3:37 p.m. |
Created at: March 9, 2026, 3:44 p.m.