Triple
T20022460
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Edward Oehler |
E494897
|
entity |
| Predicate | climbed |
P6287
|
FINISHED |
| Object | Mawenzi |
—
|
NE NERFINISHED |
How this triple was built (2 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: Mawenzi | Statement: [Edward Oehler, climbed, Mawenzi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mawenzi Context triple: [Edward Oehler, climbed, Mawenzi]
-
A.
Mawenzi
chosen
Mawenzi is the jagged, eroded eastern peak of Mount Kilimanjaro and one of its three main volcanic cones.
-
B.
Mhangura
Mhangura is a small mining town in northern Zimbabwe known historically for its copper production.
-
C.
Giriama
Giriama are a major subgroup of the Mijikenda people of coastal Kenya, known for their distinct language, cultural traditions, and historical resistance to colonial rule.
-
D.
Murang’a
Murang’a is a town in central Kenya that serves as an important commercial and cultural hub in a region historically associated with the Kikuyu community.
-
E.
Macheke
Macheke is a small town in eastern Zimbabwe situated along a major route between Harare and Mutare, known for its surrounding agricultural activities.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69da626bfd288190aa5d65098b6433ae |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e66288fc18819083833b55c5e069a6 |
completed | April 20, 2026, 5:29 p.m. |
Created at: April 11, 2026, 3:35 p.m.