Triple
T11461635
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Claude-Emma Debussy |
E271673
|
entity |
| Predicate | languageOfFamilyEnvironment |
P8532
|
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: [Claude-Emma Debussy, languageOfFamilyEnvironment, French]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageOfFamilyEnvironment Context triple: [Claude-Emma Debussy, languageOfFamilyEnvironment, French]
-
A.
languageOfFamily
chosen
Indicates the language or languages commonly used or associated with a particular family.
-
B.
parentLanguage
Indicates that one language is the ancestral or source language from which another language is derived or historically developed.
-
C.
languageFamilyContext
Indicates the broader linguistic family or grouping within which a particular language or linguistic element is situated.
-
D.
languageFamilyOf
Indicates that one entity is the language family to which the other entity (a specific language) belongs.
-
E.
languageOfAdoption
Indicates the language in which an adoption (e.g., of a text, standard, or practice) is formally made or recorded.
- 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_69d6aae0c8d881908a5a360c0be3242e |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d822f384f08190b1150ed1389dd31a |
completed | April 9, 2026, 10:06 p.m. |
| PD | Predicate disambiguation | batch_69d80867ff248190bb157fa9e355353b |
completed | April 9, 2026, 8:13 p.m. |
Created at: April 8, 2026, 9:35 p.m.