Triple
T12253459
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Andaandi |
E292034
|
entity |
| Predicate | isNotMutuallyIntelligibleWith |
P9366
|
FINISHED |
| Object | Nobiin |
E40530
|
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: Nobiin | Statement: [Andaandi, isNotMutuallyIntelligibleWith, Nobiin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nobiin Context triple: [Andaandi, isNotMutuallyIntelligibleWith, Nobiin]
-
A.
Nobiin
chosen
Nobiin is a Nile-Nubian language spoken primarily by Nubian communities in southern Egypt and northern Sudan, known for its ancient roots and rich oral tradition.
-
B.
Ninji
Ninji is a small, black, ninja-like creature from the Super Mario series known for its leaping attacks and appearances as a recurring enemy.
-
C.
Nintu
Nintu is a Mesopotamian mother goddess associated with childbirth, creation, and the formation of humankind.
-
D.
Beni
Beni is a town in western Nepal that serves as a gateway to the Dhaulagiri and Annapurna mountain regions.
-
E.
Beni
Beni is a sparsely populated, largely Amazonian department in northeastern Bolivia known for its tropical lowlands, cattle ranching, and rich indigenous cultures.
- 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_69d6ab67950c8190be08450a06228c4b |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d91cc849308190b6ff416f8b4f01e8 |
completed | April 10, 2026, 3:52 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f60abdc5988190a19104385f54fb06 |
completed | May 2, 2026, 2:31 p.m. |
Created at: April 8, 2026, 9:52 p.m.