Triple
T20952743
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chronique d’une mort annoncée |
E516016
|
entity |
| Predicate | hasLiterarySourceLanguage |
P73818
|
FINISHED |
| Object | Spanish |
—
|
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: Spanish | Statement: [Chronique d’une mort annoncée, hasLiterarySourceLanguage, Spanish]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLiterarySourceLanguage Context triple: [Chronique d’une mort annoncée, hasLiterarySourceLanguage, Spanish]
-
A.
languageOfSources
Indicates that the specified language is the language in which the referenced sources or source materials are expressed.
-
B.
hasSourceLanguageForLoanwords
Indicates that a language serves as the original source from which loanwords are borrowed into another language.
-
C.
literarySource
Indicates that one entity serves as the written or literary origin, reference, or basis for another entity.
-
D.
hasLiterarySourceMedium
Indicates that something derives from, is based on, or is expressed through a particular literary medium (such as a book, poem, or script).
-
E.
publicationLanguageOfSourceWork
chosen
Indicates the language in which the original source work was published.
- 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_69e0b4fcd678819087a304291f14330a |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6fadf85f88190924d3919b9e665e4 |
completed | April 21, 2026, 4:19 a.m. |
| PD | Predicate disambiguation | batch_69e5c9b1bae48190a845165fed1b005e |
completed | April 20, 2026, 6:37 a.m. |
Created at: April 16, 2026, 1:27 p.m.