Triple
T15490052
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pool Department |
E378657
|
entity |
| Predicate | namedAfter |
P63
|
FINISHED |
| Object |
Pool Malebo
Pool Malebo is a broad, lake-like widening of the Congo River between Kinshasa and Brazzaville in Central Africa.
|
E1160827
|
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: Pool Malebo | Statement: [Pool Department, namedAfter, Pool Malebo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pool Malebo Context triple: [Pool Department, namedAfter, Pool Malebo]
-
A.
Zoombezi Bay
Zoombezi Bay is a popular outdoor water park in Ohio known for its water slides, wave pools, and family-friendly attractions.
-
B.
Kyalami
Kyalami is a well-known suburb in the Midrand area of Johannesburg, South Africa, famous for its motor racing circuit and upmarket residential estates.
-
C.
Sindagua
Sindagua is an extinct Barbacoan language once spoken by indigenous communities in what is now southwestern Colombia.
-
D.
Kazinga Channel
Kazinga Channel is a natural waterway in western Uganda that links Lake Edward and Lake George and is renowned for its rich wildlife and scenic boat safaris.
-
E.
Beira Lake
Beira Lake is a prominent urban lake in central Colombo, Sri Lanka, known for its scenic views, religious sites, and recreational activities amid the city’s commercial district.
- 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: Pool Malebo Triple: [Pool Department, namedAfter, Pool Malebo]
Generated description
Pool Malebo is a broad, lake-like widening of the Congo River between Kinshasa and Brazzaville in Central Africa.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Pool Malebo Target entity description: Pool Malebo is a broad, lake-like widening of the Congo River between Kinshasa and Brazzaville in Central Africa.
-
A.
Zoombezi Bay
Zoombezi Bay is a popular outdoor water park in Ohio known for its water slides, wave pools, and family-friendly attractions.
-
B.
Kyalami
Kyalami is a well-known suburb in the Midrand area of Johannesburg, South Africa, famous for its motor racing circuit and upmarket residential estates.
-
C.
Sindagua
Sindagua is an extinct Barbacoan language once spoken by indigenous communities in what is now southwestern Colombia.
-
D.
Kazinga Channel
Kazinga Channel is a natural waterway in western Uganda that links Lake Edward and Lake George and is renowned for its rich wildlife and scenic boat safaris.
-
E.
Beira Lake
Beira Lake is a prominent urban lake in central Colombo, Sri Lanka, known for its scenic views, religious sites, and recreational activities amid the city’s commercial district.
- 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_69d85cd53a7c819080f5b9042c4c199e |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e03fac2af88190ac1d119e6b21dbe0 |
completed | April 16, 2026, 1:47 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff365f27c48190822254b6da504d3d |
completed | May 9, 2026, 1:27 p.m. |
| NEDg | Description generation | batch_69ff375856448190a61979dfff751f06 |
completed | May 9, 2026, 1:32 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ff382f1bbc8190810d0d825430f9ea |
completed | May 9, 2026, 1:35 p.m. |
Created at: April 10, 2026, 3:48 a.m.