Triple
T7559332
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gobernador de Cundinamarca |
E178752
|
entity |
| Predicate | tieneRelaciónCon |
P33476
|
FINISHED |
| Object | Presidente de la República de Colombia |
—
|
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: Presidente de la República de Colombia | Statement: [Gobernador de Cundinamarca, tieneRelaciónCon, Presidente de la República de Colombia]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: tieneRelaciónCon Context triple: [Gobernador de Cundinamarca, tieneRelaciónCon, Presidente de la República de Colombia]
-
A.
laterRelationWith
Indicates that one entity stands in a temporal relationship to another such that it occurs or exists at a later time than the other.
-
B.
inRelationshipWith
Indicates that two entities are mutually involved in a defined personal, romantic, or partnership relationship with each other.
-
C.
hasRelation
chosen
Indicates that there exists some specified relationship or association between two entities.
-
D.
hasNeighborRelationshipWith
Indicates that one entity is located adjacent to or directly next to another entity, sharing a neighbor relationship.
-
E.
termRelationTo
Indicates a general relational association between one term and another, without specifying the exact nature of that relationship.
- 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_69c69f2da22c8190a50942ac20af70e8 |
completed | March 27, 2026, 3:15 p.m. |
| NER | Named-entity recognition | batch_69c6f8dc7d288190a0d08ba704cc3fc2 |
completed | March 27, 2026, 9:38 p.m. |
| PD | Predicate disambiguation | batch_69c6f4dc485c819080da13e3b7f4f08f |
completed | March 27, 2026, 9:21 p.m. |
Created at: March 27, 2026, 3:50 p.m.