Triple
T25514714
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | To Father: The Letters of Sister Maria Celeste |
E639472
|
entity |
| Predicate | originalLanguageOfLetters |
P38301
|
FINISHED |
| Object | Italian |
—
|
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: Italian | Statement: [To Father: The Letters of Sister Maria Celeste, originalLanguageOfLetters, Italian]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: originalLanguageOfLetters Context triple: [To Father: The Letters of Sister Maria Celeste, originalLanguageOfLetters, Italian]
-
A.
languageOfLetters
chosen
Indicates that one entity is the language in which the other entity’s letters or written correspondence are composed.
-
B.
originalLanguageText
Indicates that a text is expressed in its original, untranslated language.
-
C.
primaryLanguageOf
Indicates that a specified language is the main or official language used by a particular entity (such as a person, organization, or region).
-
D.
originalTextLanguage
Indicates the language in which a text was originally written or created before any translation or adaptation.
-
E.
originalLanguageStatus
Indicates the status or condition of something with respect to its original language (e.g., whether it is in, derived from, or altered from the language in which it was first created).
- 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_69e75dbe32e48190a62d749a0ff2a96a |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f72921cf2c8190909bb53f78bcc890 |
completed | May 3, 2026, 10:53 a.m. |
| PD | Predicate disambiguation | batch_69f7283d8cec8190b524c144948bc4ec |
completed | May 3, 2026, 10:49 a.m. |
Created at: April 21, 2026, 2:54 p.m.