Triple
T2323099
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Borrowdale |
E48225
|
entity |
| Predicate | partOf |
P40
|
FINISHED |
| Object | Harare metropolitan area |
E252219
|
NE FINISHED |
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: Harare metropolitan area | Statement: [Borrowdale, partOf, Harare metropolitan area]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Harare metropolitan area Context triple: [Borrowdale, partOf, Harare metropolitan area]
-
A.
Harare
Harare is the largest city and main economic, political, and cultural center of Zimbabwe.
-
B.
Masvingo
Masvingo is one of Zimbabwe’s oldest urban centers, located in the country’s southeastern region near the Great Zimbabwe ruins.
-
C.
Harare Province
chosen
Harare Province is the metropolitan province in Zimbabwe that encompasses the capital city, Harare, and its surrounding urban areas.
-
D.
Bulawayo
Bulawayo is Zimbabwe’s second-largest city and a major industrial, cultural, and transport hub in the southwestern part of the country.
-
E.
Marondera
Marondera is a town in eastern Zimbabwe known as an agricultural and educational center within the Mashonaland region.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69a88aa308a88190b0b86c011fda7fce |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abc645bac081908c0b161d0ca99aaf |
completed | March 7, 2026, 6:31 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69af2b6475948190816531b026c7930c |
completed | March 9, 2026, 8:19 p.m. |
Created at: March 4, 2026, 7:49 p.m.