Triple
T7041273
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kovács |
E163516
|
entity |
| Predicate | frequencyType |
P37986
|
FINISHED |
| Object | very common surname in Hungary |
—
|
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: very common surname in Hungary | Statement: [Kovács, frequencyType, very common surname in Hungary]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: frequencyType Context triple: [Kovács, frequencyType, very common surname in Hungary]
-
A.
frequencyCategory
chosen
Indicates how often an action, event, or relationship occurs, typically by assigning it to a qualitative frequency level (e.g., rare, occasional, frequent).
-
B.
frequency
Indicates how often an event, action, or relationship occurs within a given period or context.
-
C.
frequencyClass
Indicates how often an event, action, or relation occurs, typically by assigning it to a predefined frequency category or class.
-
D.
frequencyDependsOn
Indicates that the frequency of one event, action, or state is determined or influenced by another factor or condition.
-
E.
frequencyChange
Indicates a change in how often an event, action, or state occurs over time.
- 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_69c6885e7c1c8190be32a8f79ab4e0cf |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6e4a3c36c819080942c59f1830ae8 |
completed | March 27, 2026, 8:12 p.m. |
| PD | Predicate disambiguation | batch_69c6e1bb602081908bfa6186a1f5a4b4 |
completed | March 27, 2026, 7:59 p.m. |
Created at: March 27, 2026, 2:36 p.m.