Triple
T32598706
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Miklós Nagy |
E833303
|
entity |
| Predicate | hasTypicalEthnicAssociation |
P27835
|
FINISHED |
| Object | Hungarian |
—
|
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: Hungarian | Statement: [Miklós Nagy, hasTypicalEthnicAssociation, Hungarian]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypicalEthnicAssociation Context triple: [Miklós Nagy, hasTypicalEthnicAssociation, Hungarian]
-
A.
mayBelongToEthnicGroup
Indicates that an entity is possibly, but not certainly, a member of a specified ethnic group.
-
B.
hasEthnicCharacteristic
chosen
Indicates that an entity possesses or is associated with a particular ethnic characteristic or identity.
-
C.
hasEthnicScope
Indicates that something is relevant or applicable specifically to a particular ethnic group or ethnic context.
-
D.
holderEthnicity
Indicates the ethnic background or group to which the holder of something (e.g., a document, account, or item) belongs.
-
E.
linkedToEthnicIdentity
Indicates a relationship where something is associated or connected with a particular ethnic identity.
- 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_69f3492ab63c8190aec24d5003b47c29 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69fecd0a732c819097bdd3eb69b6158c |
completed | May 9, 2026, 5:58 a.m. |
| PD | Predicate disambiguation | batch_69fecc0318d481908b5b20598a76a9fe |
completed | May 9, 2026, 5:54 a.m. |
Created at: May 1, 2026, 1:05 a.m.