Triple
T100662
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Peru |
E2033
|
entity |
| Predicate | officialLanguage |
P236
|
FINISHED |
| Object | Quechua |
E3862
|
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: Quechua | Statement: [Peru, officialLanguage, Quechua]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Quechua Context triple: [Peru, officialLanguage, Quechua]
-
A.
Quechua
chosen
Quechua is an indigenous language family of the central Andes, historically associated with the Inca Empire and still widely spoken across several South American countries.
-
B.
Aymara
Aymara is an indigenous language spoken primarily by the Aymara people of the central Andes in countries such as Bolivia, Peru, and Chile.
-
C.
Kichwa
Kichwa is a Quechuan indigenous language variety widely spoken by Andean communities in Ecuador and neighboring regions.
-
D.
Spanish
Spanish is a Romance language originating from the Iberian Peninsula that is now one of the world’s most widely spoken languages across Europe, the Americas, and beyond.
-
E.
Equatoguinean Spanish
Equatoguinean Spanish is the distinctive variety of Spanish spoken in Equatorial Guinea, shaped by local African languages and the country’s unique colonial history.
- 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_69a24e0a5b7c81908d52da08c60dabc4 |
completed | Feb. 28, 2026, 2:08 a.m. |
| NER | Named-entity recognition | batch_69a256a7957c8190bf9924eff7572b95 |
completed | Feb. 28, 2026, 2:44 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a26c1e3b688190ab90ecf5f2d55e50 |
completed | Feb. 28, 2026, 4:16 a.m. |
Created at: Feb. 28, 2026, 2:12 a.m.