Triple
T18366452
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | PE-LIM |
E440058
|
entity |
| Predicate | hasCapital |
P204
|
FINISHED |
| Object | Huacho |
—
|
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: Huacho | Statement: [PE-LIM, hasCapital, Huacho]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Huacho Context triple: [PE-LIM, hasCapital, Huacho]
-
A.
Huacho
chosen
Huacho is a coastal city in central Peru that serves as an important commercial and agricultural hub north of Lima.
-
B.
Colina
Colina is the popular nickname of the home stadium used by the Brazilian football club Nacional Futebol Clube.
-
C.
Colina
Colina is a commune and city in central Chile known for its growing residential areas and proximity to Santiago in the Santiago Metropolitan Region.
-
D.
Santiago de Chuco
Santiago de Chuco is a town in northern Peru best known as the birthplace of influential poet César Vallejo and for its Andean cultural and historical significance.
-
E.
Vilcashuamán
Vilcashuamán is a historic Andean town in Peru known for its well-preserved Inca archaeological complex, including temples, terraces, and ceremonial structures.
- 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_69d8b918221c8190a9f7b563d64ac677 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e5174e834481909453ba25561d1b1d |
completed | April 19, 2026, 5:56 p.m. |
Created at: April 10, 2026, 10:38 a.m.