Triple
T975468
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | La Vie en rose |
E21042
|
entity |
| Predicate | commonEnglishRendering |
P3437
|
FINISHED |
| Object | Life through rose-colored glasses |
—
|
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: Life through rose-colored glasses | Statement: [La Vie en rose, commonEnglishRendering, Life through rose-colored glasses]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: commonEnglishRendering Context triple: [La Vie en rose, commonEnglishRendering, Life through rose-colored glasses]
-
A.
EnglishVersionFeature
Indicates that the related item is a feature or aspect specifically associated with the English-language version of something.
-
B.
hasEnglishName
chosen
Indicates that an entity is associated with a name expressed in the English language.
-
C.
languageStandard
Indicates that one entity conforms to, is defined by, or is governed by the language rules, specifications, or conventions established by another entity as a standard.
-
D.
languageUse
Indicates the language or languages an entity uses for communication, expression, or interaction.
-
E.
hasOfficialNameInEnglish
Indicates that an entity has an officially recognized name expressed in the English language.
- 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_69a493c2b62c8190b616351789ec47f8 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b46234c88190b2bfc9cafe59d7f7 |
completed | March 1, 2026, 9:49 p.m. |
| PD | Predicate disambiguation | batch_69a4b2a6aa2c8190aebba71320ab678f |
completed | March 1, 2026, 9:41 p.m. |
Created at: March 1, 2026, 7:40 p.m.