Triple
T18074172
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kingdom of Bunyoro |
E432509
|
entity |
| Predicate | lostTerritoryTo |
P1701
|
FINISHED |
| Object |
Toro Kingdom
Toro Kingdom is a traditional Bantu monarchy in western Uganda, known for its cultural heritage and historical role as one of the successor states to the once-dominant Bunyoro Kingdom.
|
E1304424
|
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: Toro Kingdom | Statement: [Kingdom of Bunyoro, lostTerritoryTo, Toro Kingdom]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Toro Kingdom Context triple: [Kingdom of Bunyoro, lostTerritoryTo, Toro Kingdom]
-
A.
Toro So
Toro So is a specific Dogon language variety spoken by the Dogon people of Mali.
-
B.
Toro Tegu
Toro Tegu is a Dogon language spoken in Mali, known for its distinct phonology and grammar within the Dogon language family.
-
C.
Toro
Toro is the official bull-themed mascot of the NFL's Houston Texans, known for entertaining fans at games and team events.
-
D.
Toro
Toro is a Marvel Comics supervillain and member of the Invaders, often depicted as a powerful, bull-like adversary.
-
E.
Toro
Toro is the traditional nickname of Torino F.C., a historic Italian football club based in Turin.
- 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: Toro Kingdom Triple: [Kingdom of Bunyoro, lostTerritoryTo, Toro Kingdom]
Generated description
Toro Kingdom is a traditional Bantu monarchy in western Uganda, known for its cultural heritage and historical role as one of the successor states to the once-dominant Bunyoro Kingdom.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Toro Kingdom Target entity description: Toro Kingdom is a traditional Bantu monarchy in western Uganda, known for its cultural heritage and historical role as one of the successor states to the once-dominant Bunyoro Kingdom.
-
A.
Toro So
Toro So is a specific Dogon language variety spoken by the Dogon people of Mali.
-
B.
Toro Tegu
Toro Tegu is a Dogon language spoken in Mali, known for its distinct phonology and grammar within the Dogon language family.
-
C.
Toro
Toro is a Marvel Comics supervillain and member of the Invaders, often depicted as a powerful, bull-like adversary.
-
D.
Toro
Toro is the traditional nickname of Torino F.C., a historic Italian football club based in Turin.
-
E.
Toro
Toro is a historic town in the province of Zamora, Castile and León, Spain, known for its medieval architecture and wine production.
- 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_69d8b9070cac81909fa9473fb1c3f1c7 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4ccefcdc4819086d0b224731bfc4d |
completed | April 19, 2026, 12:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a03567944dc8190acf755c523ecd2fd |
completed | May 12, 2026, 4:34 p.m. |
| NEDg | Description generation | batch_6a035a643c9081909daa111f5692fed8 |
completed | May 12, 2026, 4:50 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a035ad09e18819081eed396cb445dbc |
completed | May 12, 2026, 4:52 p.m. |
Created at: April 10, 2026, 10:26 a.m.