Triple
T12541521
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chiclayo |
E299848
|
entity |
| Predicate | roadConnection |
P385
|
FINISHED |
| Object | Piura |
E295055
|
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: Piura | Statement: [Chiclayo, roadConnection, Piura]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Piura Context triple: [Chiclayo, roadConnection, Piura]
-
A.
Piura
chosen
Piura is a major city in northwestern Peru known for its colonial architecture, warm climate, and role as a commercial and agricultural hub near the Pacific coast.
-
B.
Piura Region
Piura Region is a coastal region in northwestern Peru known for its warm climate, beaches, and agricultural production.
-
C.
Tumbes
Tumbes is a coastal city in northwestern Peru near the border with Ecuador, known for its mangrove forests and tropical climate.
-
D.
Chimbote
Chimbote is a coastal city in north-central Peru known for its fishing industry and port on the Pacific Ocean.
-
E.
Arequipa
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.
- 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_69d6ada707008190aaec1238117c9379 |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d9546fc620819093335988dbab3256 |
completed | April 10, 2026, 7:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6c0d6947c819080d33199d331724c |
completed | May 3, 2026, 3:28 a.m. |
Created at: April 8, 2026, 9:57 p.m.