Triple
T27040510
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Flora Drew |
E684471
|
entity |
| Predicate | sourceLanguageOfTranslation |
P71670
|
FINISHED |
| Object | Chinese |
—
|
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: Chinese | Statement: [Flora Drew, sourceLanguageOfTranslation, Chinese]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sourceLanguageOfTranslation Context triple: [Flora Drew, sourceLanguageOfTranslation, Chinese]
-
A.
languageTranslatedFrom
chosen
Indicates that a language is the source/original language from which content has been translated into another language.
-
B.
translationSource
Indicates that one entity serves as the original text or content from which another entity is translated.
-
C.
sourceLanguageMeaning
Indicates that one entity expresses the meaning or sense of another entity in a particular source language.
-
D.
countryOfTranslation
Indicates that a work has been translated into a version intended for use in the specified country.
-
E.
indirectOriginLanguage
Indicates that something originates from a particular language, not directly but through one or more intermediate languages or sources.
- 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_69ef148193c48190bb1a0cfae6a407c4 |
completed | April 27, 2026, 7:47 a.m. |
| NER | Named-entity recognition | batch_69f625411c14819086492062e86ba8d5 |
completed | May 2, 2026, 4:24 p.m. |
| PD | Predicate disambiguation | batch_69f623a91b9c8190b2e2fdbc55cb89b6 |
completed | May 2, 2026, 4:17 p.m. |
Created at: April 27, 2026, 8:04 a.m.