Triple
T14153617
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Walo |
E350752
|
entity |
| Predicate | capital |
P234
|
FINISHED |
| Object | Nder |
E421730
|
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: Nder | Statement: [Walo, capital, Nder]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nder Context triple: [Walo, capital, Nder]
-
A.
Ndar
chosen
Ndar is the historical Wolof name for the city of Saint-Louis in Senegal, reflecting its pre-colonial and local cultural identity.
-
B.
Ngerderar
Ngerderar is a small village located within Aimeliik State in the island nation of Palau.
-
C.
Ndeʼ
Ndeʼ is the self-designation used by the Chiricahua Apache people for themselves and their language.
-
D.
Nandinha
Nandinha is a diminutive, affectionate nickname commonly used in Portuguese for someone named Fernanda.
-
E.
Nande
The Nande are a Bantu-speaking ethnic group primarily inhabiting the mountainous regions of North Kivu in the eastern Democratic Republic of the Congo, known for their farming, trade, and distinct cultural traditions.
- 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_69d8278775fc8190b0802d22ca2f495d |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de6133754881908e1e97db71772deb |
completed | April 14, 2026, 3:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fcf7ea34408190830263d7f5a88ce9 |
completed | May 7, 2026, 8:36 p.m. |
Created at: April 10, 2026, 12:57 a.m.