Triple
T334811
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Natal Colony |
E6701
|
entity |
| Predicate | namedAfter |
P63
|
FINISHED |
| Object | Natal |
E15763
|
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: Natal | Statement: [Natal Colony, namedAfter, Natal]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Natal Context triple: [Natal Colony, namedAfter, Natal]
-
A.
Natal
chosen
Natal is a historical region in southeastern South Africa, centered on the port city of Durban and known for its colonial history and diverse cultural heritage.
-
B.
Pauletta
Pauletta is a feminine given name, typically considered a diminutive or variant of Paula or Pauline.
-
C.
Palmer
Palmer is an English surname borne by numerous notable figures, including politicians, artists, and scientists, and is derived from medieval pilgrims who carried palm branches.
-
D.
Nain
Nain is a remote coastal town in northern Labrador, Canada, known as the administrative center of the Inuit region of Nunatsiavut.
-
E.
Lapa
Lapa is a historic and bohemian neighborhood in Rio de Janeiro, Brazil, famous for its vibrant nightlife, samba clubs, and iconic aqueduct arches.
- 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_69a2e79434908190a9d5afe415153ad9 |
completed | Feb. 28, 2026, 1:03 p.m. |
| NER | Named-entity recognition | batch_69a2eac641708190b85fa21368e5de8e |
completed | Feb. 28, 2026, 1:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a3f0a2d7b08190a99a85a79e69a717 |
completed | March 1, 2026, 7:54 a.m. |
Created at: Feb. 28, 2026, 1:08 p.m.