Triple
T10265185
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nguzo Saba |
E240694
|
entity |
| Predicate | hasPrinciple |
P1757
|
FINISHED |
| Object | Nia |
E609103
|
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: Nia | Statement: [Nguzo Saba, hasPrinciple, Nia]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nia Context triple: [Nguzo Saba, hasPrinciple, Nia]
-
A.
Nia
chosen
Nia is a given name commonly used as a short or familiar form of longer names such as Antonia.
-
B.
Niya
Niya is an ancient Silk Road oasis settlement in the southern Taklamakan Desert, known for its well-preserved archaeological remains that illuminate the culture and trade of the Kingdom of Khotan.
-
C.
Nikia
Nikia is a traditional whitewashed hilltop village on the Greek island of Nisyros, known for its panoramic views over the volcanic crater and the Aegean Sea.
-
D.
Nikkiya
Nikkiya is an American singer and rapper known for her collaborations in hip-hop and R&B, particularly with producer and artist K.E. on the Track (Keys).
-
E.
Nita
Nita is a feminine given name commonly used as a shortened or affectionate form of longer names such as Juanita.
- 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_69d381a94c1881908fc38fc263d9b9c2 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d25f17ec8190ac57836d36cb39db |
completed | April 7, 2026, 9:46 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d6f7ff3f808190b4a8a021f44e2176 |
completed | April 9, 2026, 12:51 a.m. |
Created at: April 6, 2026, 11:33 a.m.