Triple
T11710740
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Strength in Unity |
E278366
|
entity |
| Predicate | hasTranslationRelationWith |
P2303
|
FINISHED |
| Object | Dzala ertobashia |
—
|
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: Dzala ertobashia | Statement: [Strength in Unity, hasTranslationRelationWith, Dzala ertobashia]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTranslationRelationWith Context triple: [Strength in Unity, hasTranslationRelationWith, Dzala ertobashia]
-
A.
hasTranslation
chosen
Indicates that one entity is a translation or translated version of another entity in a different language.
-
B.
hasRelation
Indicates that there exists some specified relationship or association between two entities.
-
C.
hasTranslated
Indicates that one entity has rendered the content of another entity from one language into a different language.
-
D.
hasTranslationBase
Indicates that one entity serves as the original source or base text from which the other entity is translated.
-
E.
hasTranslationNote
Indicates that there is an explanatory note about how something has been translated, such as clarifying wording choices, alternatives, or translation issues.
- 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_69d6aaff2ce88190b4a1e4b341ad5377 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a49f072c81909c6a964a92e5bc0c |
completed | April 10, 2026, 7:19 a.m. |
| PD | Predicate disambiguation | batch_69d88a7d483081909c2a101087515d74 |
completed | April 10, 2026, 5:28 a.m. |
Created at: April 8, 2026, 9:40 p.m.