Triple
T21574151
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | al-Futuhat al-Makkiyya |
E532354
|
entity |
| Predicate | approximateVolumes |
P132864
|
FINISHED |
| Object | 37 |
—
|
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: 37 | Statement: [al-Futuhat al-Makkiyya, approximateVolumes, 37]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: approximateVolumes Context triple: [al-Futuhat al-Makkiyya, approximateVolumes, 37]
-
A.
approximateVolumeInCubicCentimetres
Indicates that one entity has an estimated or roughly calculated volume measured in cubic centimetres.
-
B.
volumeOf
Indicates the quantitative three-dimensional space occupied by an entity or contained within an object.
-
C.
approximateMass
Indicates that one entity has a mass value that is an estimate or close approximation of the mass of another entity.
-
D.
approximateEstimation
chosen
Indicates an estimation relationship where one value or assessment is only roughly or closely, but not exactly, equal to another.
-
E.
approximateSize
Indicates that one entity has a size that is roughly or approximately equal to the size of another entity.
- 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_69e0c4618bec8190bcb0feb74568cbb1 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69eee9cef2748190990a81967d49b706 |
completed | April 27, 2026, 4:45 a.m. |
| PD | Predicate disambiguation | batch_69e6320c8c2c81908bf031447d66a052 |
completed | April 20, 2026, 2:02 p.m. |
Created at: April 16, 2026, 6:30 p.m.