Triple
T19939906
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Giona |
E479279
|
entity |
| Predicate | hasLinguisticAdaptation |
P17147
|
FINISHED |
| Object | Italian form of Jonah |
—
|
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: Italian form of Jonah | Statement: [Giona, hasLinguisticAdaptation, Italian form of Jonah]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLinguisticAdaptation Context triple: [Giona, hasLinguisticAdaptation, Italian form of Jonah]
-
A.
hasLinguisticFeature
Indicates that an entity possesses a particular linguistic property, trait, or characteristic.
-
B.
hasLinguisticVariety
Indicates that one entity possesses or exhibits a particular linguistic variety in relation to another entity or context.
-
C.
hasLinguisticDomain
chosen
Indicates that something (such as a term, expression, or resource) is associated with or applies within a particular linguistic domain or language context.
-
D.
hasLinguist
Indicates that an entity is associated with or possesses a linguist, typically as a member, employee, collaborator, or resource.
-
E.
linguisticStrategy
Indicates the communicative approach or method used in language to achieve a particular interactional, rhetorical, or pragmatic goal.
- 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_69d8e522a17c819095165d4d24939fd8 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e65a19d77c819088bce99c94568d0d |
completed | April 20, 2026, 4:53 p.m. |
| PD | Predicate disambiguation | batch_69e537f47c508190853c4e009c6b5566 |
completed | April 19, 2026, 8:15 p.m. |
Created at: April 10, 2026, 1:53 p.m.