Triple
T4034241
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Amathole Mountains |
E83788
|
entity |
| Predicate | fauna |
P950
|
FINISHED |
| Object | knysna lourie |
E58257
|
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: knysna lourie | Statement: [Amathole Mountains, fauna, knysna lourie]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: knysna lourie Context triple: [Amathole Mountains, fauna, knysna lourie]
-
A.
Knysna
chosen
Knysna is a picturesque coastal town in South Africa known for its lagoon, indigenous forests, and role as a major tourist destination along the Garden Route.
-
B.
Ruimsig
Ruimsig is a suburban residential area in Roodepoort, west of Johannesburg, known for its golf course, botanical gardens, and family-oriented lifestyle.
-
C.
Kamieskroon
Kamieskroon is a small town in South Africa’s Northern Cape, known as a gateway to the wildflower displays and rugged landscapes of the Namaqualand region.
-
D.
Maroelap
Maroelap is the former name of Maloelap Atoll, a coral atoll in the Ratak Chain of the Marshall Islands in the central Pacific Ocean.
-
E.
Lanseria
Lanseria is a town in the northwestern part of Johannesburg, South Africa, known primarily for hosting the privately owned Lanseria International Airport.
- 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_69aed92f7cf0819098e0539bdcc3767f |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefb11d92481909aaebbc250ff45b9 |
completed | March 9, 2026, 4:53 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5563e11708190abc9ba55b1be43a5 |
completed | March 14, 2026, 12:36 p.m. |
Created at: March 9, 2026, 3:36 p.m.