Triple
T34666908
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Four Kinds |
E890280
|
entity |
| Predicate | correspondsToTerm |
P128211
|
FINISHED |
| Object | Arba Minim |
—
|
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: Arba Minim | Statement: [Four Kinds, correspondsToTerm, Arba Minim]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: correspondsToTerm Context triple: [Four Kinds, correspondsToTerm, Arba Minim]
-
A.
correspondsWith
Indicates that two entities are in mutual alignment or agreement, such that one matches, parallels, or is equivalent to the other in a specified respect.
-
B.
relatedToTerm
Indicates a general, non-specific relationship or association between one term and another.
-
C.
containsCorrespondenceWith
Indicates that one entity includes or holds correspondence (such as messages or communications) that is associated with or exchanged with another entity.
-
D.
hasTerm
Indicates that an entity includes, is associated with, or is defined by a specific term or condition.
-
E.
value1CorrespondsTo
chosen
Indicates that one value is directly associated with, matches, or maps to another value in a defined correspondence.
- 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_69f7805ce6208190ac6dbd9c97989978 |
completed | May 3, 2026, 5:05 p.m. |
| PD | Predicate disambiguation | batch_69f77956ec648190ba4fb7e9d83fd107 |
completed | May 3, 2026, 4:35 p.m. |
Created at: May 1, 2026, 2:05 a.m.