Triple
T33344091
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Post-Office Girl |
E853748
|
entity |
| Predicate | firstEnglishTranslationLanguage |
P206423
|
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: [The Post-Office Girl, firstEnglishTranslationLanguage, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstEnglishTranslationLanguage Context triple: [The Post-Office Girl, firstEnglishTranslationLanguage, English]
-
A.
firstEuropeanPublicationLanguage
Indicates the language in which an entity was first published in Europe.
-
B.
firstEnglishTranslationYear
Indicates the year in which an entity was first translated into English.
-
C.
firstMajorEuropeanTranslationLanguage
Indicates the language into which a work was first translated in a major European context.
-
D.
firstEditionLanguage
Indicates the language in which a work was originally published in its first edition.
-
E.
wasFirstLatinTranslationBy
Indicates that one entity is the earliest Latin translation of another entity, produced by a specified translator or source.
- 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_69f3496a1a588190bad9cbe9221144e0 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_6a037c9141dc819098d7fcc36e69882c |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379f505c88190ac0879ab422c3054 |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c7fb9f88190b384b1b68200aef0 |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 1, 2026, 1:34 a.m.