Triple
T7723195
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Champenois language |
E175063
|
entity |
| Predicate | hasTraditionalUseIn |
P68064
|
FINISHED |
| Object | songs and storytelling |
—
|
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: songs and storytelling | Statement: [Champenois language, hasTraditionalUseIn, songs and storytelling]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTraditionalUseIn Context triple: [Champenois language, hasTraditionalUseIn, songs and storytelling]
-
A.
traditionalUse
Indicates that something is used or practiced according to long-established customs, habits, or cultural traditions.
-
B.
hasUseInTradition
chosen
Indicates that something is employed or holds a functional role within a particular cultural, religious, or historical tradition.
-
C.
traditionallyUsedBy
Indicates that something has been customarily or historically used by a particular person, group, or culture over time.
-
D.
traditionalUseDomain
Indicates that something is traditionally used or applied within a particular domain, field, or area of practice.
-
E.
medicinalUse
Indicates that one entity is used as a treatment or remedy for a disease, condition, or health-related purpose affecting another 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_69c6995d541c81909eaa646b1a8369a9 |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c7074eca4c8190bd51fd1b450729e8 |
completed | March 27, 2026, 10:40 p.m. |
| PD | Predicate disambiguation | batch_69c7016a6cf88190b53bf4b958f0f302 |
completed | March 27, 2026, 10:15 p.m. |
Created at: March 27, 2026, 4:05 p.m.