Triple
T1289393
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Isha |
E27509
|
entity |
| Predicate | legalClassification |
P13138
|
FINISHED |
| Object | individual obligation (fard ayn) |
—
|
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: individual obligation (fard ayn) | Statement: [Isha, legalClassification, individual obligation (fard ayn)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: legalClassification Context triple: [Isha, legalClassification, individual obligation (fard ayn)]
-
A.
legalConcept
Indicates a relationship where something is classified or treated as a concept defined and governed by law or legal theory.
-
B.
legalCodeType
Indicates the specific category or classification of a legal code that applies to an entity or situation.
-
C.
legalCase
Indicates a relationship where a formal legal dispute or proceeding exists between parties, typically adjudicated by a court or similar authority.
-
D.
legalCharacterization
chosen
Indicates how an action, event, or situation is classified or characterized under a specific legal framework or set of laws.
-
E.
typeOfLaw
Indicates that one entity is a specific category or kind of law to which the other entity pertains.
- 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_69a496d4ec448190ad653b2590c46711 |
completed | March 1, 2026, 7:43 p.m. |
| NER | Named-entity recognition | batch_69a4c0d4dfb081908c8825d6062b1d99 |
completed | March 1, 2026, 10:42 p.m. |
| PD | Predicate disambiguation | batch_69a4bee41ca08190b0ad6f7ea40c0b62 |
completed | March 1, 2026, 10:34 p.m. |
Created at: March 1, 2026, 7:51 p.m.