Triple
T25189031
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Márk |
E630808
|
entity |
| Predicate | hasStressPatternInHungarian |
P4253
|
FINISHED |
| Object | stress on first syllable |
—
|
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: stress on first syllable | Statement: [Márk, hasStressPatternInHungarian, stress on first syllable]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasStressPatternInHungarian Context triple: [Márk, hasStressPatternInHungarian, stress on first syllable]
-
A.
hasStressPattern
chosen
Indicates that an entity (such as a word or phrase) follows a particular arrangement of stressed and unstressed units (e.g., syllables) in its pronunciation.
-
B.
hasGivenNameFormInHungarian
Indicates that an entity’s given name is expressed in its specific Hungarian linguistic form.
-
C.
hasVowelHarmony
Indicates that the phonological vowels in a word or morpheme conform to a systematic harmony pattern (e.g., all front or all back vowels) according to the language’s vowel harmony rules.
-
D.
hasSyllableStructure
Indicates that an entity (typically a word or morpheme) possesses a particular arrangement or pattern of syllables.
-
E.
hasSyllabicStructure
Indicates that an entity possesses a specific arrangement or pattern of syllables, such as their number, order, or type.
- 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_69e75a8a6d088190ba1e82a4345225e7 |
completed | April 21, 2026, 11:07 a.m. |
| NER | Named-entity recognition | batch_69f661b58ac48190907b6c6e9ccc2c59 |
completed | May 2, 2026, 8:42 p.m. |
| PD | Predicate disambiguation | batch_69f660eea4648190b0d5e24293607813 |
completed | May 2, 2026, 8:39 p.m. |
Created at: April 21, 2026, 12:44 p.m.