Triple
T3742925
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Machloket |
E79742
|
entity |
| Predicate | isAnalyzedIn |
P34153
|
FINISHED |
| Object | yeshiva study |
—
|
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: yeshiva study | Statement: [Machloket, isAnalyzedIn, yeshiva study]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isAnalyzedIn Context triple: [Machloket, isAnalyzedIn, yeshiva study]
-
A.
analyzes
Indicates that one entity systematically examines or evaluates another entity to understand its nature, structure, or components.
-
B.
helpsAnalyze
Indicates that one entity assists another in examining, interpreting, or understanding something in a more detailed or effective way.
-
C.
unitOfAnalysis
Indicates the primary entity, level, or component that is being examined or measured in a given analysis or study.
-
D.
difficultToAnalyzeAs
Indicates that one entity is hard to examine, interpret, or understand when considered in terms of, or compared to, another entity.
-
E.
isObservedIn
chosen
Indicates that something (such as a phenomenon, property, or behavior) is detected, recorded, or found to occur within a particular context, setting, or environment.
- 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_69ad8b115610819095b02007da5ca3cb |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69adcb563fac8190b6a55580d0386e8a |
completed | March 8, 2026, 7:17 p.m. |
| PD | Predicate disambiguation | batch_69adc048f28c819092bed16a95a3cac1 |
completed | March 8, 2026, 6:30 p.m. |
Created at: March 8, 2026, 3:34 p.m.