Triple
T4648787
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | much-enduring |
E102237
|
entity |
| Predicate | translationOfType |
P20094
|
FINISHED |
| Object | epic epithet for Odysseus |
—
|
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: epic epithet for Odysseus | Statement: [much-enduring, translationOfType, epic epithet for Odysseus]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: translationOfType Context triple: [much-enduring, translationOfType, epic epithet for Odysseus]
-
A.
translationOn
Indicates that one entity is a translation of another entity, typically expressing the same content in a different language or linguistic form.
-
B.
translationMethod
Indicates the technique or process used to translate content from one language or form to another.
-
C.
translationDirection
Indicates the source and target languages involved in a translation, specifying the direction from the original language to the translated language.
-
D.
translationTargetLanguage
Indicates the language into which content is being or has been translated.
-
E.
typeOfTranslation
chosen
Indicates that one entity is a specific kind or category of translation in relation to 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_69bd43d71a308190afea7280841b0de8 |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd6632708c8190b627d99363ab062c |
completed | March 20, 2026, 3:22 p.m. |
| PD | Predicate disambiguation | batch_69bd620fc5e081908325ac8e6a6384ab |
completed | March 20, 2026, 3:04 p.m. |
Created at: March 20, 2026, 1:14 p.m.