Triple
T1010392
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Busch Gardens Tampa Bay |
E21808
|
entity |
| Predicate | hasRollerCoaster |
P23566
|
FINISHED |
| Object |
Kumba
Kumba is a renowned steel roller coaster at Busch Gardens Tampa Bay, famous for its intense inversions and smooth, high-speed layout.
|
E136502
|
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: Kumba | Statement: [Busch Gardens Tampa Bay, hasRollerCoaster, Kumba]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kumba Context triple: [Busch Gardens Tampa Bay, hasRollerCoaster, Kumba]
-
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.
Kibondo
Kibondo is a town in western Tanzania that serves as an administrative and commercial center in the Kigoma Region.
-
C.
Gombe
Gombe is a region in western Tanzania best known for its national park where pioneering primatologist Jane Goodall conducted her landmark chimpanzee research.
-
D.
Gombe
Gombe is a major city in northeastern Nigeria that serves as the capital and economic hub of Gombe State.
-
E.
Garki
Garki is a prominent administrative and commercial district in Nigeria’s capital city, Abuja, housing numerous government offices, businesses, and residential areas.
- 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: Kumba Triple: [Busch Gardens Tampa Bay, hasRollerCoaster, Kumba]
Generated description
Kumba is a renowned steel roller coaster at Busch Gardens Tampa Bay, famous for its intense inversions and smooth, high-speed layout.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Kumba Target entity description: Kumba is a renowned steel roller coaster at Busch Gardens Tampa Bay, famous for its intense inversions and smooth, high-speed layout.
-
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.
Kibondo
Kibondo is a town in western Tanzania that serves as an administrative and commercial center in the Kigoma Region.
-
C.
Gombe
Gombe is a region in western Tanzania best known for its national park where pioneering primatologist Jane Goodall conducted her landmark chimpanzee research.
-
D.
Gombe
Gombe is a major city in northeastern Nigeria that serves as the capital and economic hub of Gombe State.
-
E.
Garki
Garki is a prominent administrative and commercial district in Nigeria’s capital city, Abuja, housing numerous government offices, businesses, and residential areas.
- 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_69a493c68e24819080ed0ee8bcfd5ce0 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4bb71e7f88190bf33bbe5ef2c68ff |
completed | March 1, 2026, 10:19 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac763582c48190bcf038162a1dea1c |
completed | March 7, 2026, 7:02 p.m. |
| NEDg | Description generation | batch_69ac770141a88190b71552d46fb4d2ad |
completed | March 7, 2026, 7:05 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ac777a7768819098b9d4dd771a6750 |
completed | March 7, 2026, 7:07 p.m. |
Created at: March 1, 2026, 7:41 p.m.