Triple
T29252892
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Écureuil |
E741613
|
entity |
| Predicate | marketNameLanguage |
P171807
|
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: [Écureuil, marketNameLanguage, French]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: marketNameLanguage Context triple: [Écureuil, marketNameLanguage, French]
-
A.
languageOfPrimaryMarkets
Indicates the primary language or languages used in the main markets where an entity operates or targets its products or services.
-
B.
primaryLanguageMarket
Indicates that a particular language is the main or dominant language used within a given market or market segment.
-
C.
marketNameInEurope
Indicates the name under which a product or entity is marketed specifically in European markets.
-
D.
brandLanguageVariant
Indicates that one language variant of a brand is related to or derived from another language version of the same brand.
-
E.
languageOfAds
Indicates that the specified language is used in the advertisements associated with the given entity.
- F. None of above. chosen
Provenance (4 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_69f0911eba2c8190b07cd2fdf91422c9 |
completed | April 28, 2026, 10:51 a.m. |
| NER | Named-entity recognition | batch_69f6a28c7c148190bfc980aad9f678ca |
completed | May 3, 2026, 1:19 a.m. |
| PD | Predicate disambiguation | batch_69f69fe1e3c88190830bb2e9f407357e |
completed | May 3, 2026, 1:07 a.m. |
| PDg | Predicate description generation | batch_69f6a28b8ea881908733485374771c51 |
completed | May 3, 2026, 1:19 a.m. |
Created at: April 28, 2026, 12:35 p.m.