Triple
T18331128
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | El Patrón |
E439141
|
entity |
| Predicate | usedAsCharacterEpithetIn |
P71235
|
FINISHED |
| Object | crime documentaries about Pablo Escobar |
—
|
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: crime documentaries about Pablo Escobar | Statement: [El Patrón, usedAsCharacterEpithetIn, crime documentaries about Pablo Escobar]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedAsCharacterEpithetIn Context triple: [El Patrón, usedAsCharacterEpithetIn, crime documentaries about Pablo Escobar]
-
A.
epithetAppliedBy
Indicates that a particular epithet or descriptive label is used or assigned by a specific agent to a target entity.
-
B.
hasMeaningOfEpithet
Indicates that one entity expresses or conveys the meaning or sense of another entity’s epithet.
-
C.
oftenUsedAsNameFor
chosen
Indicates that something frequently serves as a name or designation for another entity.
-
D.
hasCharacterNamedAfter
Indicates that one entity has a character whose name is derived from or intentionally based on another entity.
-
E.
associatedWithEpithet
Indicates that an entity is linked to or described by a particular epithet or descriptive label.
- 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_69d8b9175fec8190af865699b4e64d8c |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e50eca08388190b4e757a5f63b5d41 |
completed | April 19, 2026, 5:20 p.m. |
| PD | Predicate disambiguation | batch_69e44fe91bc08190906518e1b120fcf0 |
completed | April 19, 2026, 3:45 a.m. |
Created at: April 10, 2026, 10:36 a.m.