Triple
T35119626
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ser Rodrik Cassel |
E1014129
|
entity |
| Predicate | trainsInSkill |
P137368
|
FINISHED |
| Object | basic combat tactics |
—
|
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: basic combat tactics | Statement: [Ser Rodrik Cassel, trainsInSkill, basic combat tactics]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: trainsInSkill Context triple: [Ser Rodrik Cassel, trainsInSkill, basic combat tactics]
-
A.
trainsInDiscipline
chosen
Indicates that one entity undergoes training or instruction within a particular discipline, field, or area of expertise associated with another entity.
-
B.
alsoTrains
Indicates that an entity, in addition to its primary role or activity, is involved in training another entity.
-
C.
maintainsTrainsFor
Indicates that one entity is responsible for servicing, repairing, or otherwise keeping trains operational for another entity.
-
D.
trainsForOccupation
Indicates that an entity undergoes training or preparation aimed at qualifying for or performing a specific occupation.
-
E.
indicatesSkill
Indicates a relationship where one entity possesses, demonstrates, or is associated with a particular skill represented by another entity.
- 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_69f76dd8b6948190aaa32b081816bd94 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f78f63c8788190b253a18de5ca1312 |
completed | May 3, 2026, 6:09 p.m. |
| PD | Predicate disambiguation | batch_69f78e2d71248190b850c2802ec170c0 |
completed | May 3, 2026, 6:04 p.m. |
Created at: May 3, 2026, 4:01 p.m.