Triple
T18199879
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hungarian orthography |
E435753
|
entity |
| Predicate | usesSpecialStatusLettersPrimarilyFor |
P117325
|
FINISHED |
| Object | foreign words |
—
|
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: foreign words | Statement: [Hungarian orthography, usesSpecialStatusLettersPrimarilyFor, foreign words]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesSpecialStatusLettersPrimarilyFor Context triple: [Hungarian orthography, usesSpecialStatusLettersPrimarilyFor, foreign words]
-
A.
usesSpecialLetterFor
chosen
Indicates that one entity employs a particular special letter or character specifically in relation to another entity.
-
B.
usesAdditionalLettersFrom
Indicates that one entity forms or derives its representation by incorporating extra letters taken from another entity beyond those originally present.
-
C.
isPrimarilyUsedAs
Indicates that one entity serves mainly or most commonly in the role, function, or purpose specified by the other entity.
-
D.
usedPrimarilyIn
Indicates that something is mainly or most commonly employed within a particular context, domain, or purpose.
-
E.
usesLetteredServices
Indicates that an entity makes use of services that are identified or categorized by letter-based designations.
- 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_69d8b90dba6481908e119eb9aa4ca0cb |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4e0d610f88190b4f69b1c433ea6b1 |
completed | April 19, 2026, 2:04 p.m. |
| PD | Predicate disambiguation | batch_69e4331e92408190ad607ba4956a3897 |
completed | April 19, 2026, 1:42 a.m. |
Created at: April 10, 2026, 10:31 a.m.