Triple
T15787708
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Block script (Ktav Ashuri) |
E382779
|
entity |
| Predicate | hasCantillationMarks |
P67250
|
FINISHED |
| Object | Hebrew te'amim |
—
|
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 te'amim | Statement: [Block script (Ktav Ashuri), hasCantillationMarks, Hebrew te'amim]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCantillationMarks Context triple: [Block script (Ktav Ashuri), hasCantillationMarks, Hebrew te'amim]
-
A.
usesToneMarks
chosen
Indicates that one entity applies or includes diacritical tone marks in the representation or transcription of another entity (such as text, language, or symbols).
-
B.
hasSyllabary
Indicates that one entity possesses or is associated with a specific syllabary writing system used to represent its language or notation.
-
C.
hasLyricsTone
Indicates the tonal quality or emotional character expressed by the lyrics of a piece of music.
-
D.
hasLyricalVariant
Indicates that one item has an alternative version that differs in its lyrics while remaining related to the original.
-
E.
hasLyricCharacter
Indicates that a musical work or song includes a specific character or persona within its lyrics.
- 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.