Triple
T15824609
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Béla |
E383704
|
entity |
| Predicate | frequencyInHistory |
P119784
|
FINISHED |
| Object | common among medieval Hungarian rulers |
—
|
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: common among medieval Hungarian rulers | Statement: [Béla, frequencyInHistory, common among medieval Hungarian rulers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: frequencyInHistory Context triple: [Béla, frequencyInHistory, common among medieval Hungarian rulers]
-
A.
frequencyInAntiquity
Indicates how often something occurred, appeared, or was used during ancient times.
-
B.
frequencyCategory
Indicates how often an action, event, or relationship occurs, typically by assigning it to a qualitative frequency level (e.g., rare, occasional, frequent).
-
C.
frequencyContent
Indicates that one entity specifies or characterizes the rate or frequency with which the content or occurrence of another entity takes place.
-
D.
frequencyClass
Indicates how often an event, action, or relation occurs, typically by assigning it to a predefined frequency category or class.
-
E.
frequencyComparedTo
Indicates how often one event or action occurs relative to another, expressing a comparison of their frequencies.
- F. None of above. chosen
Provenance (4 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_69d86da34c888190976e06c4019d415a |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e11e5f46748190acb46cc482501307 |
completed | April 16, 2026, 5:37 p.m. |
| PD | Predicate disambiguation | batch_69e005418f588190824d91ff7974dada |
completed | April 15, 2026, 9:38 p.m. |
| PDg | Predicate description generation | batch_69e007647f908190adb178c68c7bb7cf |
completed | April 15, 2026, 9:47 p.m. |
Created at: April 10, 2026, 4:49 a.m.