Triple
T5811839
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Catholic University of Santa María |
E128884
|
entity |
| Predicate | servesCommunity |
P82
|
FINISHED |
| Object | Arequipa metropolitan area |
E22142
|
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: Arequipa metropolitan area | Statement: [Catholic University of Santa María, servesCommunity, Arequipa metropolitan area]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Arequipa metropolitan area Context triple: [Catholic University of Santa María, servesCommunity, Arequipa metropolitan area]
-
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.
Chivay
Chivay is a small Andean town in southern Peru that serves as the main gateway and service hub for visitors to the Colca Canyon.
-
D.
Huacho
Huacho is a coastal city in central Peru that serves as an important commercial and agricultural hub north of Lima.
-
E.
Chimbote
Chimbote is a coastal city in north-central Peru known for its fishing industry and port on the Pacific Ocean.
- 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_69c0084788848190bcf71f6bc5d71597 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c02b54c2848190bb85212689d0b511 |
completed | March 22, 2026, 5:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c11343ef288190922d6992e0519636 |
completed | March 23, 2026, 10:17 a.m. |
Created at: March 22, 2026, 3:52 p.m.