Triple
T20402366
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zaña |
E500367
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | northern Peru |
—
|
NE NERFINISHED |
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: northern Peru | Statement: [Zaña, locatedIn, northern Peru]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: northern Peru Context triple: [Zaña, locatedIn, northern Peru]
-
A.
northern Peru
chosen
Northern Peru is a geographic region of Peru known for its Andean highlands, rich pre-Columbian archaeological sites, and diverse coastal and jungle landscapes.
-
B.
southeastern Peru
Southeastern Peru is a region of the country that includes the historic Andean area around Cusco and extends toward the Amazon Basin.
-
C.
western Peru
Western Peru is the coastal and Andean region of Peru that includes major urban centers such as Lima and is characterized by arid Pacific shores and the western slopes of the Andes.
-
D.
eastern Peru
Eastern Peru is a remote, sparsely populated region dominated by Amazon rainforest, extensive river systems, and rich biodiversity.
-
E.
Southern Peru
Southern Peru is a geographic region of Peru known for its Andean highlands, volcanic landscapes, and major cities such as Arequipa and Cusco.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b4a81bec8190b69adfdc1336a015 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6798fc3b88190a372c34102bfaa6f |
completed | April 20, 2026, 7:07 p.m. |
Created at: April 16, 2026, 11:29 a.m.