Triple
T100660
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Peru |
E2033
|
entity |
| Predicate | largestCity |
P235
|
FINISHED |
| Object | Lima |
E2605
|
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: Lima | Statement: [Peru, largestCity, Lima]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lima Context triple: [Peru, largestCity, Lima]
-
A.
Lima
chosen
Lima is the capital and largest city of Peru, known as a major political, economic, and cultural center on South America's Pacific coast.
-
B.
Guayaquil
Guayaquil is a major Pacific port city in southwestern Ecuador and the country’s principal commercial and industrial center.
-
C.
Santiago
Santiago is the capital and primary economic, political, and cultural center of Chile, located in the country’s central valley.
-
D.
Santiago
Santiago was one of the smaller support vessels in Ferdinand Magellan’s early 16th-century expedition to circumnavigate the globe, primarily used for scouting and exploration along the South American coast.
-
E.
Valparaíso
Valparaíso is a major Pacific port city in central Chile, renowned for its steep hillsides, colorful houses, historic funiculars, and UNESCO-listed historic quarter.
- 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_69a2e3bbb3508190870d3291a836923e |
completed | Feb. 28, 2026, 12:46 p.m. |
Created at: Feb. 28, 2026, 2:12 a.m.