Triple
T22504871
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Worldline SA |
E556362
|
entity |
| Predicate | languageOfHeadquarters |
P33549
|
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: [Worldline SA, languageOfHeadquarters, French]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageOfHeadquarters Context triple: [Worldline SA, languageOfHeadquarters, French]
-
A.
standardLanguageOf
Indicates that one entity serves as the officially recognized or commonly used standard language for another entity (such as a country, region, or organization).
-
B.
languageOfCommunications
chosen
Indicates that a specified language is used as the medium for communications associated with an entity or interaction.
-
C.
languageOfFounders
Indicates the language or languages spoken or used by the founders of an entity.
-
D.
governingCountryLanguage
Indicates that a particular language is officially used or recognized by the governing authorities of a given country.
-
E.
capitalLanguage
Indicates that the specified language is the primary or official language used in the capital city of a given entity.
- 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_69e11e555edc81909ca803587dafd747 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15d5ac5808190a66f9111c350f4dc |
completed | April 29, 2026, 1:22 a.m. |
| PD | Predicate disambiguation | batch_69e898be31448190be5ae7f5656f0497 |
completed | April 22, 2026, 9:45 a.m. |
Created at: April 16, 2026, 8:50 p.m.