Triple
T5829482
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Divan of Hafez |
E129308
|
entity |
| Predicate | hasTranslationIn |
P45244
|
FINISHED |
| Object | English |
—
|
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: English | Statement: [Divan of Hafez, hasTranslationIn, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTranslationIn Context triple: [Divan of Hafez, hasTranslationIn, English]
-
A.
hasTranslation
Indicates that one entity is a translation or translated version of another entity in a different language.
-
B.
hasTranslationNote
Indicates that there is an explanatory note about how something has been translated, such as clarifying wording choices, alternatives, or translation issues.
-
C.
hasWorkTranslatedInto
chosen
Indicates that a work has been translated into a specified language or target work.
-
D.
hasLanguageOn
Indicates that an entity uses or is associated with a particular language in a specific context, medium, or location.
-
E.
languageOfTranslations
Indicates that one entity is the language into which another entity (such as a text or work) has been translated.
- 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_69c00849d55481908b4f9f5543e0bf6d |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c044ab0a048190b84be40fb13c0f50 |
completed | March 22, 2026, 7:36 p.m. |
| PD | Predicate disambiguation | batch_69c03341e5888190a5f219b6f92cb161 |
completed | March 22, 2026, 6:21 p.m. |
Created at: March 22, 2026, 3:54 p.m.