Triple
T929386
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Francesco Petrarca |
E20056
|
entity |
| Predicate | wroteInLanguage |
P11300
|
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: [Francesco Petrarca, wroteInLanguage, Italian]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wroteInLanguage Context triple: [Francesco Petrarca, wroteInLanguage, Italian]
-
A.
writtenIn
Indicates that a work (such as a text, program, or document) is expressed or encoded using a particular language or notation.
-
B.
languageOfWritings
Indicates that a specified language is the one in which certain writings or written works are composed.
-
C.
wroteInMultipleLanguages
Indicates that an entity authored written works using more than one language.
-
D.
isLanguageOf
Indicates that a particular language is used as the official or primary language associated with a given entity (such as a person, document, or region).
-
E.
wroteIn
chosen
Indicates that an entity authored or composed something using a particular language, medium, or writing system.
- 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_69a493af3dc48190adb7263e6e445ea1 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4b34775ac8190aabbd047a36cec6b |
completed | March 1, 2026, 9:44 p.m. |
| PD | Predicate disambiguation | batch_69a4b29876348190a29f4ff9878074a5 |
completed | March 1, 2026, 9:41 p.m. |
Created at: March 1, 2026, 7:40 p.m.