Triple
T27073316
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Puerto Santander |
E685386
|
entity |
| Predicate | partOfDepartmentCapitalRegion |
P78503
|
FINISHED |
| Object | metropolitan area of Cúcuta |
—
|
LITERAL 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: metropolitan area of Cúcuta | Statement: [Puerto Santander, partOfDepartmentCapitalRegion, metropolitan area of Cúcuta]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: partOfDepartmentCapitalRegion Context triple: [Puerto Santander, partOfDepartmentCapitalRegion, metropolitan area of Cúcuta]
-
A.
belongsToDepartmentCapitalRegion
chosen
Indicates that an entity is part of, or administratively assigned to, the capital region of a department.
-
B.
capitalOfDepartment
Indicates that a city or town serves as the administrative capital of a specified department (an administrative division).
-
C.
hasDepartmentCapital
Indicates that a department has a specific city designated as its capital.
-
D.
hasCapitalRegionRelation
Indicates a relationship where one entity serves as the capital region or administrative capital area of another entity.
-
E.
hasCountryCapitalOfDepartment
Indicates that a specific country serves as the capital or primary governing nation associated with a particular department.
- 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_69ef14843b1481909d828b3d5a44550a |
completed | April 27, 2026, 7:47 a.m. |
| NER | Named-entity recognition | batch_69fd0b92f42881908cd77e3f058adcc2 |
completed | May 7, 2026, 10 p.m. |
| PD | Predicate disambiguation | batch_69fd0a3d68d4819094d92040f7c48d7c |
completed | May 7, 2026, 9:55 p.m. |
Created at: April 27, 2026, 8:29 a.m.