Triple
T15787707
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Block script (Ktav Ashuri) |
E382779
|
entity |
| Predicate | hasDiacriticsSystem |
P86767
|
FINISHED |
| Object | Hebrew niqqud |
—
|
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: Hebrew niqqud | Statement: [Block script (Ktav Ashuri), hasDiacriticsSystem, Hebrew niqqud]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDiacriticsSystem Context triple: [Block script (Ktav Ashuri), hasDiacriticsSystem, Hebrew niqqud]
-
A.
usesDiacritics
Indicates that the referenced text or linguistic element employs diacritical marks as part of its written form.
-
B.
hasAccentSystem
Indicates that an entity employs or is characterized by a particular system or pattern of accents (e.g., in language, music, or typography).
-
C.
usesDiacriticsFrom
chosen
Indicates that one entity employs or incorporates the diacritical marks that originate from or are characteristic of another entity.
-
D.
hasPunctuationSystem
Indicates that an entity possesses or employs a system of punctuation marks for structuring written language.
-
E.
diacriticType
Indicates the specific kind or category of diacritic mark associated with a character or symbol.
- 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_69d86da16e188190b89af699f1ed0bfe |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e0540380448190a025338f0e62e6d1 |
completed | April 16, 2026, 3:14 a.m. |
| PD | Predicate disambiguation | batch_69e00537bd1c81908d6e832792fd934f |
completed | April 15, 2026, 9:37 p.m. |
Created at: April 10, 2026, 4:48 a.m.