Triple
T27035853
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rani Hladni rat |
E681048
|
entity |
| Predicate | karakteriziraGa |
P662
|
FINISHED |
| Object | utrka u naoružanju |
—
|
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: utrka u naoružanju | Statement: [Rani Hladni rat, karakteriziraGa, utrka u naoružanju]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: karakteriziraGa Context triple: [Rani Hladni rat, karakteriziraGa, utrka u naoružanju]
-
A.
karakter
Indicates that one entity is a character (e.g., a role or persona) associated with or embodied by another entity.
-
B.
characterizedBy
chosen
Indicates that one entity possesses a defining quality, feature, or attribute expressed by another entity.
-
C.
hatCharakter
Indicates that an entity possesses or exhibits a particular character, trait, or quality.
-
D.
titleCharacterization
Indicates how a title characterizes, describes, or frames an associated entity (such as a work, person, or concept).
-
E.
ruleCharacterization
Indicates that one rule is described, defined, or characterized in terms of another rule or set of rules.
- 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_69eeeb5566f08190813daf896fa3da04 |
completed | April 27, 2026, 4:51 a.m. |
| NER | Named-entity recognition | batch_69f62d53ad58819080c5227c7a729d15 |
completed | May 2, 2026, 4:58 p.m. |
| PD | Predicate disambiguation | batch_69f62c15952881908a5ea0c25904afec |
completed | May 2, 2026, 4:53 p.m. |
Created at: April 27, 2026, 7:16 a.m.