Triple
T10102171
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lands of the Crown of Saint Stephen |
E216227
|
entity |
| Predicate | multiethnic |
P42257
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Lands of the Crown of Saint Stephen, multiethnic, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: multiethnic Context triple: [Lands of the Crown of Saint Stephen, multiethnic, true]
-
A.
hasEthnicallyMixedPopulation
chosen
Indicates that a population is composed of people from multiple distinct ethnic groups rather than being ethnically homogeneous.
-
B.
ethnicPluralityOf
Indicates that one ethnic group constitutes the largest share of the population within a given place or entity, though not necessarily an absolute majority.
-
C.
minority
Indicates that one entity belongs to a smaller, less represented, or non-dominant group within a larger population or context.
-
D.
includesMixedSexRace
Indicates that the group or context involves individuals of more than one sex and more than one race.
-
E.
isMulticulturalCity
Indicates that a city is characterized by the presence and interaction of multiple cultural, ethnic, or linguistic communities.
- 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_69ca83d039f08190b9d10363221c69fb |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cdd099c21c819097aac4f0f168a2da |
completed | April 2, 2026, 2:12 a.m. |
| PD | Predicate disambiguation | batch_69cd4b9b853c8190a2af993ce9b21309 |
completed | April 1, 2026, 4:45 p.m. |
Created at: March 30, 2026, 9:02 p.m.