Triple
T711411
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Arabian Nights |
E14213
|
entity |
| Predicate | firstMajorEuropeanTranslationLanguage |
P19778
|
FINISHED |
| Object | French |
—
|
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: French | Statement: [The Arabian Nights, firstMajorEuropeanTranslationLanguage, French]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstMajorEuropeanTranslationLanguage Context triple: [The Arabian Nights, firstMajorEuropeanTranslationLanguage, French]
-
A.
firstEnglishTranslators
Indicates that the subject is among the earliest individuals or groups to translate the object into English.
-
B.
firstCompleteBibleTranslationBy
Indicates that an entity is the first person or group to have completed a full translation of a particular Bible into a given language or form.
-
C.
firstEnglishTranslationYear
Indicates the year in which an entity was first translated into English.
-
D.
languageOfEarliestForm
Indicates the language in which the earliest known form or attested version of something (e.g., a text, name, or expression) is recorded.
-
E.
historicalLanguage
Indicates that one language is a historical or earlier form/ancestor of another language.
- F. None of above. chosen
Provenance (4 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_69a4934a36e081909e7abef98b898a4e |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a77fcc6881908a025bb21e44ad56 |
completed | March 1, 2026, 8:54 p.m. |
| PD | Predicate disambiguation | batch_69a4a4f221b081909fbaa689fb20eb3e |
completed | March 1, 2026, 8:43 p.m. |
| PDg | Predicate description generation | batch_69a4a77e42e081909a6f2d1bfdc78ef0 |
completed | March 1, 2026, 8:54 p.m. |
Created at: March 1, 2026, 7:36 p.m.