Triple
T14681722
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tu B'Av |
E344802
|
entity |
| Predicate | fastingStatus |
P111698
|
FINISHED |
| Object | fasting not practiced |
—
|
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: fasting not practiced | Statement: [Tu B'Av, fastingStatus, fasting not practiced]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fastingStatus Context triple: [Tu B'Av, fastingStatus, fasting not practiced]
-
A.
fastingStatusOfParticipants
chosen
Indicates whether participants are in a fasting state or not at the time relevant to the study or measurement.
-
B.
fastingDuration
Indicates the length of time that an entity abstains from eating (and possibly drinking), typically as part of a fasting practice.
-
C.
typeOfFasting
Indicates the specific kind or category of fasting practice associated with an entity.
-
D.
hasFastingRule
Indicates that there is a prescribed rule or requirement regarding fasting that applies to the subject.
-
E.
fastingIncludes
Indicates that a period of fasting encompasses or contains a specified component, practice, or time interval as part of that fast.
- 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_69d822e34b348190ada4d1cdb6c7c226 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb56a51ec8190941684fd562a7182 |
completed | April 14, 2026, 9:45 p.m. |
| PD | Predicate disambiguation | batch_69de6579fb7881909becc8f5822b39d4 |
completed | April 14, 2026, 4:04 p.m. |
Created at: April 10, 2026, 1:28 a.m.