Triple
T3099302
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Grace After Meals |
E64675
|
entity |
| Predicate | secondBlessing |
P20739
|
FINISHED |
| Object | Al HaAretz VeAl HaMazon |
—
|
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: Al HaAretz VeAl HaMazon | Statement: [Grace After Meals, secondBlessing, Al HaAretz VeAl HaMazon]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: secondBlessing Context triple: [Grace After Meals, secondBlessing, Al HaAretz VeAl HaMazon]
-
A.
blessedBy
chosen
Indicates that one entity has conferred a blessing, favor, or sacred endorsement upon another entity.
-
B.
secondPrecept
Indicates that an entity adheres to or is governed by the second precept, rule, or moral injunction within a defined set of precepts.
-
C.
secondedBy
Indicates that an initial proposal, motion, or action by one entity is formally supported or endorsed by another entity as a second.
-
D.
secondTemptation
Indicates a relationship where an entity is subjected to or engages in a second instance of temptation, following an initial tempting event.
-
E.
secondBowlEffect
Indicates the phenomenon where consuming a second bowl of food leads to a different (often diminished or altered) effect compared to the first bowl.
- 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_69ad857dc98481909e585dc3372e3ed5 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada269a9188190aada5b3799d4dfd7 |
completed | March 8, 2026, 4:23 p.m. |
| PD | Predicate disambiguation | batch_69ad9df06ed88190809f0683122caa5a |
completed | March 8, 2026, 4:04 p.m. |
Created at: March 8, 2026, 3:03 p.m.