Triple
T22136031
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Parisian salon at Rue de Courcelles |
E547030
|
entity |
| Predicate | languageOfConversation |
P18209
|
FINISHED |
| Object | French |
—
|
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: French | Statement: [Parisian salon at Rue de Courcelles, languageOfConversation, French]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageOfConversation Context triple: [Parisian salon at Rue de Courcelles, languageOfConversation, French]
-
A.
languageDiscussedIn
Indicates that a particular language is the topic of discussion within a specified context, source, or discourse.
-
B.
languageUse
chosen
Indicates the language or languages an entity uses for communication, expression, or interaction.
-
C.
languageLabel
Indicates the human-readable name or label of a language associated with an entity or resource.
-
D.
languageOfExpression
Indicates that a particular language is used as the medium or form in which an expression (such as a text, utterance, or work) is realized.
-
E.
languagePair
Indicates a relationship that associates two specific languages as a paired combination, typically for translation, comparison, or mapping between them.
- 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_69e11e3a95d88190a3bd80d9471976c3 |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f129b9ee54819081141c4f28e1211a |
completed | April 28, 2026, 9:42 p.m. |
| PD | Predicate disambiguation | batch_69e71b384e008190b723c9a0f1089d66 |
completed | April 21, 2026, 6:37 a.m. |
Created at: April 16, 2026, 8:32 p.m.