Triple
T8701303
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kololo Hill |
E206537
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object |
Naguru
Naguru is a residential and commercial neighborhood in Kampala, Uganda, known for its hilltop location, embassies, and mixed-income housing.
|
E751789
|
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: Naguru | Statement: [Kololo Hill, locatedNear, Naguru]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Naguru Context triple: [Kololo Hill, locatedNear, Naguru]
-
A.
Negombo
Negombo is a coastal city in western Sri Lanka known historically as a strategic colonial port and today for its fishing industry and beach tourism.
-
B.
Kepez
Kepez is a populous district and municipality within the city of Antalya in southern Turkey, known for its residential areas and growing urban infrastructure.
-
C.
Lanseria
Lanseria is a town in the northwestern part of Johannesburg, South Africa, known primarily for hosting the privately owned Lanseria International Airport.
-
D.
Dimetoka
Dimetoka is a historic town in present-day northeastern Greece, known for its medieval and Ottoman heritage.
-
E.
Barawa
Barawa is a West Chadic language spoken in parts of Nigeria, belonging to the Afroasiatic language family.
- 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: Naguru Triple: [Kololo Hill, locatedNear, Naguru]
Generated description
Naguru is a residential and commercial neighborhood in Kampala, Uganda, known for its hilltop location, embassies, and mixed-income housing.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Naguru Target entity description: Naguru is a residential and commercial neighborhood in Kampala, Uganda, known for its hilltop location, embassies, and mixed-income housing.
-
A.
Negombo
Negombo is a coastal city in western Sri Lanka known historically as a strategic colonial port and today for its fishing industry and beach tourism.
-
B.
Kepez
Kepez is a populous district and municipality within the city of Antalya in southern Turkey, known for its residential areas and growing urban infrastructure.
-
C.
Lanseria
Lanseria is a town in the northwestern part of Johannesburg, South Africa, known primarily for hosting the privately owned Lanseria International Airport.
-
D.
Dimetoka
Dimetoka is a historic town in present-day northeastern Greece, known for its medieval and Ottoman heritage.
-
E.
Barawa
Barawa is a West Chadic language spoken in parts of Nigeria, belonging to the Afroasiatic language family.
- 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_69ca83555b6c8190abe930dd397e863b |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc58b38cf88190bfdcbac9c340cb96 |
completed | March 31, 2026, 11:28 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cef41657588190ba6f79c27658dd1b |
completed | April 2, 2026, 10:56 p.m. |
| NEDg | Description generation | batch_69cef8292f4c81909098f1205b6b5595 |
completed | April 2, 2026, 11:13 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69cef8c6e0c08190b1810f00cb4cc304 |
completed | April 2, 2026, 11:16 p.m. |
Created at: March 30, 2026, 6:34 p.m.