Triple
T13220320
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kaddish for an Unborn Child |
E314734
|
entity |
| Predicate | languageOfEnglishTranslation |
P21151
|
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: [Kaddish for an Unborn Child, languageOfEnglishTranslation, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageOfEnglishTranslation Context triple: [Kaddish for an Unborn Child, languageOfEnglishTranslation, English]
-
A.
languageOfTranslations
Indicates that one entity is the language into which another entity (such as a text or work) has been translated.
-
B.
EnglishTranslation
Indicates that one expression is the English-language translation equivalent of another expression.
-
C.
languageTranslatedFrom
Indicates that a language is the source/original language from which content has been translated into another language.
-
D.
languageEquivalent
Indicates that two linguistic expressions convey the same meaning or function across different languages or language varieties.
-
E.
translationTargetLanguage
chosen
Indicates the language into which content is being or 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_69d806affc688190a25b6ccc588e9c72 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d98cf581508190883033f0c961736a |
completed | April 10, 2026, 11:51 p.m. |
| PD | Predicate disambiguation | batch_69d98bc938f081909f123bdf1263ff7f |
completed | April 10, 2026, 11:46 p.m. |
Created at: April 9, 2026, 9:18 p.m.