Triple
T1433582
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Meccan surahs |
E30505
|
entity |
| Predicate | hasApproximateCount |
P20367
|
FINISHED |
| Object | around 86 surahs |
—
|
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: around 86 surahs | Statement: [Meccan surahs, hasApproximateCount, around 86 surahs]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasApproximateCount Context triple: [Meccan surahs, hasApproximateCount, around 86 surahs]
-
A.
hasApproximateMemberCount
chosen
Indicates that an entity is associated with a group or collection for which only an estimated or non-exact number of members is known.
-
B.
hasApproximateValue
Indicates that one entity’s value is close to, but not exactly equal to, the value of another entity within an acceptable margin of error.
-
C.
hasApproximateExtent
Indicates that one entity has a spatial, temporal, or quantitative extent that is only roughly or approximately specified rather than exact.
-
D.
approximateCapacity
Indicates that one entity has an estimated or rough capacity value relative to another or to a specified measure.
-
E.
hasApproximateDepth
Indicates that an entity is associated with a depth value that is not exact but estimated or approximate.
- 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_69a498fc69ec8190b61722bd4b67c4d2 |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c500a9888190a16fbb1ec97a79c9 |
completed | March 1, 2026, 11 p.m. |
| PD | Predicate disambiguation | batch_69a4c4771c9481908ae47c959debbe77 |
completed | March 1, 2026, 10:57 p.m. |
Created at: March 1, 2026, 8 p.m.