Triple
T22853856
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pacanga District |
E566424
|
entity |
| Predicate | hasCountry |
P846
|
FINISHED |
| Object | 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: Peru | Statement: [Pacanga District, hasCountry, Peru]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Peru Context triple: [Pacanga District, hasCountry, Peru]
-
A.
Peru
chosen
Peru is a South American country known for its rich Inca heritage, diverse landscapes from Andes mountains to Amazon rainforest, and the iconic archaeological site of Machu Picchu.
-
B.
Peru
Peru is a small rural town in Berkshire County, Massachusetts, known for its elevated terrain and quiet, forested landscape in western New England.
-
C.
Iperu
Iperu is a prominent town in Ogun State, southwestern Nigeria, known as an important commercial and cultural center of the Remo region.
-
D.
Şile
Şile is a coastal district on the Black Sea known for its beaches, lighthouse, and traditional Şile cloth, located on the Asian side of Istanbul, Turkey.
-
E.
Equador
Equador is a small municipality in the state of Rio Grande do Norte in Brazil, known for its rural character and location within the Central Potiguar mesoregion.
- 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_69e2458750b481908a8e4cf4609cc6cf |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f17eba65a881908c484262c3ee5212 |
completed | April 29, 2026, 3:44 a.m. |
Created at: April 17, 2026, 3:37 p.m.