Triple
T34676304
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mihaly |
E890502
|
entity |
| Predicate | diacriticForm |
P134206
|
FINISHED |
| Object | Mihály |
—
|
NE NERFINISHED |
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: Mihály | Statement: [Mihaly, diacriticForm, Mihály]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: diacriticForm Context triple: [Mihaly, diacriticForm, Mihály]
-
A.
diacriticForms
chosen
Indicates that one written form is a diacritic variant or includes diacritic marks relative to another form.
-
B.
diacriticFunction
Indicates that a diacritic serves a particular role or effect in relation to the base character or linguistic unit it modifies.
-
C.
diacriticType
Indicates the specific kind or category of diacritic mark associated with a character or symbol.
-
D.
diacriticCharacter
Indicates a relationship where one character is a diacritic mark that modifies the pronunciation or meaning of another base character.
-
E.
diacriticStrippedForm
Indicates that one textual form is derived from another by removing all diacritic marks (such as accents or umlauts) from its characters.
- 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_69f349d9c59481908b36baa0be093aea |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f723241a188190bc3e8b2236279511 |
completed | May 3, 2026, 10:27 a.m. |
| PD | Predicate disambiguation | batch_69f72157af108190880317a62e634bb0 |
completed | May 3, 2026, 10:20 a.m. |
Created at: May 1, 2026, 2:05 a.m.