Triple
T7719924
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shlomo Ganzfried |
E174980
|
entity |
| Predicate | hasWorkInSubject |
P73996
|
FINISHED |
| Object | daily Jewish law observance |
—
|
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: daily Jewish law observance | Statement: [Shlomo Ganzfried, hasWorkInSubject, daily Jewish law observance]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasWorkInSubject Context triple: [Shlomo Ganzfried, hasWorkInSubject, daily Jewish law observance]
-
A.
hasWorkAsSubject
Indicates that an entity serves as the subject (creator or originator) of a particular work or creative output.
-
B.
hasWorkSubject
Indicates that a work (such as a document, artwork, or project) is about or concerns a particular subject or topic.
-
C.
hasWorkOn
Indicates that one entity is associated with, contributes to, or performs work on another entity (such as a project, task, or artifact).
-
D.
hasWorkBy
Indicates that one entity (such as a collection, exhibition, or publication) includes or contains creative works produced by another entity (such as an artist, author, or creator).
-
E.
hasWorkField
chosen
Indicates that an entity is associated with or operates within a particular field or area of work.
- 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_69c6995d541c81909eaa646b1a8369a9 |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c702eedc088190be645c029dfc462a |
completed | March 27, 2026, 10:21 p.m. |
| PD | Predicate disambiguation | batch_69c701683dec8190be9861e592aa8ce0 |
completed | March 27, 2026, 10:15 p.m. |
Created at: March 27, 2026, 4:05 p.m.