Triple
T2775426
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cape Province |
E61556
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Namaqualand |
E66609
|
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: Namaqualand | Statement: [Cape Province, contains, Namaqualand]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Namaqualand Context triple: [Cape Province, contains, Namaqualand]
-
A.
Namaqualand
chosen
Namaqualand is a semi-desert region in southwestern Africa famed for its spectacular seasonal wildflower displays and unique biodiversity.
-
B.
Karoo
The Karoo is a vast semi-arid region in South Africa characterized by sparse vegetation, unique succulent flora, and extreme temperature variations.
-
C.
Simpson Desert
The Simpson Desert is a vast, arid dune desert in central Australia known for its parallel red sand dunes and remote, sparsely inhabited landscape.
-
D.
Great Sandy Desert
The Great Sandy Desert is a vast, remote desert region in northwestern Australia characterized by extensive sand dunes, arid climate, and sparse population.
-
E.
Kalahari Desert
The Kalahari Desert is a vast semi-arid sandy savanna in southern Africa known for its red dunes, sparse vegetation, and unique wildlife adapted to its dry conditions.
- 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_69ab4b7cd13481909174bca9809ed259 |
completed | March 6, 2026, 9:47 p.m. |
| NER | Named-entity recognition | batch_69abdd81015481908785fbef0326a2db |
completed | March 7, 2026, 8:10 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69afc64c83748190921589bec20dec58 |
completed | March 10, 2026, 7:20 a.m. |
Created at: March 6, 2026, 9:57 p.m.