Triple
T36428280
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kling |
E897366
|
entity |
| Predicate | isInOnomasticField |
P132798
|
FINISHED |
| Object | anthroponymy |
—
|
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: anthroponymy | Statement: [Kling, isInOnomasticField, anthroponymy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isInOnomasticField Context triple: [Kling, isInOnomasticField, anthroponymy]
-
A.
hasOnomasticField
Indicates a relationship where something is associated with a specific onomastic field, i.e., a domain or category related to names or naming conventions.
-
B.
hasOnomasticRelation
Indicates that there is a relationship between entities based on names, naming patterns, or shared onomastic (name-related) features.
-
C.
isOccupationalOrToponymic
Indicates that a name or term is derived either from an occupation (job or role) or from a place (toponymic origin).
-
D.
partOfOnomasticsCategory
chosen
Indicates that one concept or term belongs to, or is classified under, a specific category within the field of onomastics (the study of names).
-
E.
isPatronymicOrToponymic
Indicates that a name or term is derived either from a person's name (patronymic) or from a place name (toponymic).
- 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_69f76e559b10819099d6655a6e14587c |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7be9d07ac8190adf796cbef60daf6 |
completed | May 3, 2026, 9:31 p.m. |
| PD | Predicate disambiguation | batch_69f7bcccd7988190aa5c931ff347d33c |
completed | May 3, 2026, 9:23 p.m. |
Created at: May 3, 2026, 4:10 p.m.