Triple
T8664431
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Central Vancouver Island |
E205629
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Ladysmith |
E199691
|
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: Ladysmith | Statement: [Central Vancouver Island, contains, Ladysmith]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ladysmith Context triple: [Central Vancouver Island, contains, Ladysmith]
-
A.
Ladysmith
Ladysmith is a South African town in KwaZulu-Natal best known as a key site of the Second Boer War, particularly the famous Siege of Ladysmith.
-
B.
Ladysmith
chosen
Ladysmith is a small coastal town on Vancouver Island in British Columbia, Canada, known for its historic downtown and scenic harbor.
-
C.
Lobamba
Lobamba is the traditional and legislative capital of Eswatini, serving as the seat of the Swazi monarchy and key national institutions.
-
D.
Kommetjie
Kommetjie is a small coastal village on South Africa’s Cape Peninsula known for its surf breaks, long white beaches, and relaxed seaside atmosphere.
-
E.
Tambo
Tambo is a South African surname most prominently associated with anti-apartheid leader Oliver Tambo.
- 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_69ca83516ae88190aefe034b3bc589e3 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc48a0ae108190b33dadcc3cb18949 |
completed | March 31, 2026, 10:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cecd0d95ec81908669ee35f0987be7 |
completed | April 2, 2026, 8:09 p.m. |
Created at: March 30, 2026, 6:30 p.m.