Triple
T31134981
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | NATO armored units |
E793613
|
entity |
| Predicate | trainedAccordingTo |
P175282
|
FINISHED |
| Object | NATO tactical procedures |
—
|
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: NATO tactical procedures | Statement: [NATO armored units, trainedAccordingTo, NATO tactical procedures]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: trainedAccordingTo Context triple: [NATO armored units, trainedAccordingTo, NATO tactical procedures]
-
A.
trainedAs
Indicates that one entity has received education or instruction to perform the role, profession, or function represented by another entity.
-
B.
isTrainedBy
Indicates that one entity receives training, instruction, or coaching from another entity.
-
C.
providesTrainingFor
Indicates that one entity delivers or conducts training activities intended to develop the skills or knowledge of another entity.
-
D.
trainedNear
Indicates that one entity received training at a location that is geographically close to another specified entity or location.
-
E.
alsoTrains
Indicates that an entity, in addition to its primary role or activity, is involved in training another entity.
- F. None of above. chosen
Provenance (4 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_69f224d2b3a48190aa9dd26fbf6eab1a |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f6cee547108190ad3bc84297d8f516 |
completed | May 3, 2026, 4:28 a.m. |
| PD | Predicate disambiguation | batch_69f6cc1188708190b8f0f56e595e6057 |
completed | May 3, 2026, 4:16 a.m. |
| PDg | Predicate description generation | batch_69f6cee3604c81908a07eade2f39064e |
completed | May 3, 2026, 4:28 a.m. |
Created at: April 29, 2026, 9:05 p.m.