Triple
T12274426
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lautaro |
E292553
|
entity |
| Predicate | learnedFrom |
P32131
|
FINISHED |
| Object | Spanish military practices |
—
|
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: Spanish military practices | Statement: [Lautaro, learnedFrom, Spanish military practices]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: learnedFrom Context triple: [Lautaro, learnedFrom, Spanish military practices]
-
A.
learn
chosen
Indicates that an entity acquires knowledge, skills, or understanding from another entity, source, or experience.
-
B.
lessonsLearned
Indicates that certain insights, knowledge, or understanding have been gained from a prior experience, event, or process.
-
C.
teachableFrom
Indicates that one entity can be taught or learned from another entity, capturing a directional teachability or learnability relationship between them.
-
D.
learnsLanguageFrom
Indicates that one entity acquires or improves knowledge of a language through instruction, exposure, or guidance provided by another entity.
-
E.
coachedFrom
Indicates that one entity served as a coach or trainer for another entity during a specified period or context.
- 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_69d6ab6856488190b5d31178d5015f8e |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d9380a5e78819086bd4dfe9a83d1f5 |
completed | April 10, 2026, 5:48 p.m. |
| PD | Predicate disambiguation | batch_69d91c4a66cc819083ce6fcaf5042af6 |
completed | April 10, 2026, 3:50 p.m. |
Created at: April 8, 2026, 9:52 p.m.