Triple
T13362956
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mount Kenya National Park |
E318863
|
entity |
| Predicate | includesPeak |
P53629
|
FINISHED |
| Object |
Lenana
Lenana is one of the main summits of Mount Kenya, popular with trekkers as the highest point accessible without technical climbing.
|
E1037822
|
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: Lenana | Statement: [Mount Kenya National Park, includesPeak, Lenana]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lenana Context triple: [Mount Kenya National Park, includesPeak, Lenana]
-
A.
Moingwena
The Moingwena were a Native American group historically associated with the Illinois (Illiniwek) confederation in the central Mississippi River region.
-
B.
Matamela
Matamela is the first given name of South African president Cyril Ramaphosa, reflecting his full birth name Matamela Cyril Ramaphosa.
-
C.
Hlengwe
Hlengwe is a regional dialect of the Tsonga language spoken by Tsonga communities in parts of southern Africa.
-
D.
Fana
Fana is a South African actor and politician known for his roles in films such as "Hotel Rwanda" and "World War Z."
-
E.
Fana
Fana is an Etruscan goddess, likely associated with nature, fertility, or sacred groves within the ancient Etruscan religious pantheon.
- 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: Lenana Triple: [Mount Kenya National Park, includesPeak, Lenana]
Generated description
Lenana is one of the main summits of Mount Kenya, popular with trekkers as the highest point accessible without technical climbing.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Lenana Target entity description: Lenana is one of the main summits of Mount Kenya, popular with trekkers as the highest point accessible without technical climbing.
-
A.
Moingwena
The Moingwena were a Native American group historically associated with the Illinois (Illiniwek) confederation in the central Mississippi River region.
-
B.
Matamela
Matamela is the first given name of South African president Cyril Ramaphosa, reflecting his full birth name Matamela Cyril Ramaphosa.
-
C.
Hlengwe
Hlengwe is a regional dialect of the Tsonga language spoken by Tsonga communities in parts of southern Africa.
-
D.
Fana
Fana is a South African actor and politician known for his roles in films such as "Hotel Rwanda" and "World War Z."
-
E.
Fana
Fana is an Etruscan goddess, likely associated with nature, fertility, or sacred groves within the ancient Etruscan religious pantheon.
- 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_69d806b7bbac8190b85278c87fa7aff3 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69da628affd081909f1790d333f0eef4 |
completed | April 11, 2026, 3:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7267c99788190b158b1d9f57ceba2 |
completed | May 3, 2026, 10:42 a.m. |
| NEDg | Description generation | batch_69f72a92211481909ddc9e45b6a3a488 |
completed | May 3, 2026, 10:59 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f72b869a8c81908d3d6e05c80d89cf |
completed | May 3, 2026, 11:03 a.m. |
Created at: April 9, 2026, 9:32 p.m.