Triple
T29514569
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Deportivo Pereira |
E748755
|
entity |
| Predicate | cityInDepartment |
P101811
|
FINISHED |
| Object | Risaralda Department |
—
|
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: Risaralda Department | Statement: [Deportivo Pereira, cityInDepartment, Risaralda Department]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: cityInDepartment Context triple: [Deportivo Pereira, cityInDepartment, Risaralda Department]
-
A.
cityLocatedInDepartment
chosen
Indicates that a city is geographically and administratively situated within a specific department.
-
B.
capitalOfDepartment
Indicates that a city or town serves as the administrative capital of a specified department (an administrative division).
-
C.
prefectureOfDepartment
Indicates that a given prefecture administers or is the capital authority of a specified department.
-
D.
hasCountryCapitalOfDepartment
Indicates that a specific country serves as the capital or primary governing nation associated with a particular department.
-
E.
capitalOfArrondissement
Indicates that a place serves as the administrative capital (seat) of a specified arrondissement.
- F. None of above.
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_69f0bd461c208190bec20bbf24e02cc5 |
completed | April 28, 2026, 1:59 p.m. |
| NER | Named-entity recognition | batch_69f66c62719c8190852726ede476e159 |
completed | May 2, 2026, 9:28 p.m. |
| PD | Predicate disambiguation | batch_69f6633ac8a88190ab0cda62bbfcf9b0 |
completed | May 2, 2026, 8:48 p.m. |
Created at: April 28, 2026, 4:35 p.m.