Triple
T1557115
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Surah Al-Isra |
E33231
|
entity |
| Predicate | hasJuzRange |
P30309
|
FINISHED |
| Object | 15–17 |
—
|
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: 15–17 | Statement: [Surah Al-Isra, hasJuzRange, 15–17]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasJuzRange Context triple: [Surah Al-Isra, hasJuzRange, 15–17]
-
A.
hasRange
Indicates that a property or relation is constrained to take its values from a specified class, type, or value set.
-
B.
hasVerseRange
Indicates a relationship where a text or passage is associated with a specific contiguous range of verses it spans.
-
C.
rangeOf
Indicates that one entity specifies the set of possible values (range) that another entity’s outputs or properties can take.
-
D.
hasDayNumberRange
Indicates that something is associated with a contiguous range of day numbers between a specified minimum and maximum value.
-
E.
hasStandardSubdivisionRange
Indicates that there is a defined range of standard subdivisions applicable to a given entity or classification.
- F. None of above. chosen
Provenance (4 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_69a885ef9cf48190b0af0f5ce3d02231 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a9407d9d1481909597af97b16512cc |
completed | March 5, 2026, 8:36 a.m. |
| PD | Predicate disambiguation | batch_69a907b688d081908171f89010c53973 |
completed | March 5, 2026, 4:33 a.m. |
| PDg | Predicate description generation | batch_69a9407aa20881909e747f247ccec642 |
completed | March 5, 2026, 8:36 a.m. |
Created at: March 4, 2026, 7:27 p.m.