Triple
T19942032
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Leviticus 17 |
E479328
|
entity |
| Predicate | penaltyDescribed |
P78296
|
FINISHED |
| Object | being cut off from the people |
—
|
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: being cut off from the people | Statement: [Leviticus 17, penaltyDescribed, being cut off from the people]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: penaltyDescribed Context triple: [Leviticus 17, penaltyDescribed, being cut off from the people]
-
A.
penaltyProvision
Indicates that a rule, contract, or law includes a clause specifying a punishment or sanction for non-compliance or violation.
-
B.
penaltyRules
Indicates the rules or conditions under which penalties are defined, applied, or enforced in a given context.
-
C.
punishmentPolicyDescribedBy
Indicates that a punishment policy is documented, specified, or explained by a particular description or source.
-
D.
punishmentDescribedAs
chosen
Indicates that one entity characterizes, labels, or portrays a punishment using a particular description or term.
-
E.
penaltyMechanism
Indicates a relationship where a rule, system, or process imposes a negative consequence or sanction in response to certain actions or conditions.
- 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_69d8e522a17c819095165d4d24939fd8 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e65a6318848190a1dd3e0a6fea3fe2 |
completed | April 20, 2026, 4:54 p.m. |
| PD | Predicate disambiguation | batch_69e537f47c508190853c4e009c6b5566 |
completed | April 19, 2026, 8:15 p.m. |
Created at: April 10, 2026, 1:54 p.m.