Triple
T18328233
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Avenida Arequipa |
E439067
|
entity |
| Predicate | namedAfter |
P63
|
FINISHED |
| Object | Arequipa city |
—
|
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: Arequipa city | Statement: [Avenida Arequipa, namedAfter, Arequipa city]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Arequipa city Context triple: [Avenida Arequipa, namedAfter, Arequipa city]
-
A.
Arequipa
chosen
Arequipa is Peru’s second-largest city, known for its colonial architecture built from white volcanic stone and its dramatic setting beneath the Misti volcano.
-
B.
Juliaca
Juliaca is a major commercial and transportation hub in southern Peru, known for its bustling markets and proximity to Lake Titicaca.
-
C.
Cusco
Cusco is a historic city in southeastern Peru that served as the capital of the Inca Empire and is now a major gateway to Machu Picchu.
-
D.
Chimbote
Chimbote is a coastal city in north-central Peru known for its fishing industry and port on the Pacific Ocean.
-
E.
city of Puno
The city of Puno is a Peruvian urban center on the shores of Lake Titicaca, known as a cultural hub of the Andean highlands and a major site of traditional festivals and folklore.
- 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_69d8b916a2d081909e249e4902f6aad9 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e50aac14488190840b9c22209f13d1 |
completed | April 19, 2026, 5:02 p.m. |
Created at: April 10, 2026, 10:36 a.m.