Triple
T4545914
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | llanero cavalry |
E110046
|
entity |
| Predicate | trainingOrigin |
P57643
|
FINISHED |
| Object | skills from cattle herding |
—
|
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: skills from cattle herding | Statement: [llanero cavalry, trainingOrigin, skills from cattle herding]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: trainingOrigin Context triple: [llanero cavalry, trainingOrigin, skills from cattle herding]
-
A.
trainingUse
Indicates that something is used for training purposes, such as preparing, educating, or improving the skills or performance of an entity.
-
B.
trainingLeadsTo
Indicates that a process of training results in or brings about a particular outcome, state, or effect.
-
C.
trainingSupport
Indicates that one entity provides assistance, resources, or facilitation to help another entity conduct or participate in training activities.
-
D.
training
Indicates that one entity is teaching, coaching, or otherwise helping another entity acquire or improve a skill, behavior, or capability.
-
E.
trainingVersion
Indicates that one entity is a specific training iteration, release, or configuration derived from or associated with 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_69bd4412524c8190be5bcc9ddee91848 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd57d761cc8190a7c8bdef6d130b5d |
completed | March 20, 2026, 2:21 p.m. |
| PD | Predicate disambiguation | batch_69bd5220e40481908ca2d7e2c43d8531 |
completed | March 20, 2026, 1:56 p.m. |
| PDg | Predicate description generation | batch_69bd56f6e75481909c487a94a2c2d0ba |
completed | March 20, 2026, 2:17 p.m. |
Created at: March 20, 2026, 1:05 p.m.