Triple
T5067632
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gustavo Gaviria |
E114181
|
entity |
| Predicate | portrayed as |
P55200
|
FINISHED |
| Object | key strategist in Narcos |
—
|
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: key strategist in Narcos | Statement: [Gustavo Gaviria, portrayed as, key strategist in Narcos]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: portrayed as Context triple: [Gustavo Gaviria, portrayed as, key strategist in Narcos]
-
A.
portrayedAsFrom
Indicates that one entity is depicted or represented as originating from, or belonging to, the place or source specified by another entity.
-
B.
portrayedVia
Indicates that one entity is represented, depicted, or expressed through a particular medium, method, or channel.
-
C.
portraysActorAs
Indicates that one entity depicts or represents an actor in a particular role, character, or manner.
-
D.
wasPortrayedAs
chosen
Indicates that one entity has been depicted or represented in the form or role of another entity, typically within some medium or context.
-
E.
portrayalLedTo
Indicates that one entity’s portrayal of another caused or significantly contributed to a subsequent outcome, reaction, or state involving that other entity.
- 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_69bd443cf28c8190ad371d603563dbdd |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd749bf69c819093e75dce56f1c0ab |
completed | March 20, 2026, 4:23 p.m. |
| PD | Predicate disambiguation | batch_69bd715622b48190a3e8e49a5ef62b4a |
completed | March 20, 2026, 4:09 p.m. |
Created at: March 20, 2026, 1:38 p.m.