Triple
T10835112
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Copiapó Airport |
E255732
|
entity |
| Predicate | hasCityServed |
P3936
|
FINISHED |
| Object | Copiapó |
E34766
|
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: Copiapó | Statement: [Copiapó Airport, hasCityServed, Copiapó]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Copiapó Context triple: [Copiapó Airport, hasCityServed, Copiapó]
-
A.
Copiapó
chosen
Copiapó is a city in northern Chile known as a regional mining center and gateway to the Atacama Desert.
-
B.
Chacala
Chacala is a small coastal village and beach destination on Mexico’s Pacific coast in the state of Nayarit, known for its tranquil atmosphere, surfing, and ecotourism.
-
C.
Chiguayante
Chiguayante is a Chilean city located near Concepción, known as part of the Greater Concepción metropolitan area in the south-central part of the country.
-
D.
Yelapa
Yelapa is a small, secluded beach village on Mexico’s Pacific coast known for its laid-back atmosphere, scenic bay setting, and appeal as an off-the-beaten-path getaway.
-
E.
Cucunubá
Cucunubá is a small colonial-era town in the Cundinamarca department of Colombia, known for its traditional wool textiles and scenic Andean highland landscapes.
- 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_69d6aa81a5d08190aa86689061d1ddd2 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d74425447081908fb51c7edf54af67 |
completed | April 9, 2026, 6:16 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e154a582188190af96ae0d5cc08dc4 |
completed | April 16, 2026, 9:29 p.m. |
Created at: April 8, 2026, 9:19 p.m.