Triple
T36993172
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | School of the Americas |
E915158
|
entity |
| Predicate | trainingTopics |
P62557
|
FINISHED |
| Object | counter-narcotics operations |
—
|
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: counter-narcotics operations | Statement: [School of the Americas, trainingTopics, counter-narcotics operations]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: trainingTopics Context triple: [School of the Americas, trainingTopics, counter-narcotics operations]
-
A.
trainingConcept
chosen
Indicates that one entity serves as a concept, topic, or subject matter that is being taught or trained on in relation to another entity.
-
B.
coveredTopics
Indicates that certain subjects or themes have been addressed or included within a discussion, document, or activity.
-
C.
trainingIn
Indicates that one entity is undergoing or receiving training within the context, program, or domain specified by another entity.
-
D.
typicalCourseTopic
Indicates that a given topic is commonly or characteristically covered as part of a particular course.
-
E.
trainingSupport
Indicates that one entity provides assistance, resources, or facilitation to help another entity conduct or participate in training activities.
- 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_69f76e8f1a8c81909db172ed31304971 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fb154c0fe08190a2e41e7a29b6055f |
completed | May 6, 2026, 10:17 a.m. |
| PD | Predicate disambiguation | batch_69f9fecc005c8190be082a8689193745 |
completed | May 5, 2026, 2:29 p.m. |
Created at: May 3, 2026, 4:14 p.m.