Triple
T4266061
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Egyptian cubit |
E96826
|
entity |
| Predicate | approximateSubunitCount |
P32237
|
FINISHED |
| Object | 7 palms per cubit |
—
|
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: 7 palms per cubit | Statement: [Egyptian cubit, approximateSubunitCount, 7 palms per cubit]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: approximateSubunitCount Context triple: [Egyptian cubit, approximateSubunitCount, 7 palms per cubit]
-
A.
minorUnitSubdivisions
Indicates that one administrative or organizational unit is subdivided into smaller, subordinate units.
-
B.
minorUnitsPerUnit
chosen
Indicates the number of smaller sub-units that collectively make up one whole unit in a given measurement or currency system.
-
C.
subunitRatio
Indicates the proportional relationship between the quantities or sizes of different subunits within a larger whole.
-
D.
numberOfUnits
Indicates the quantity or count of discrete units associated with an entity or relationship.
-
E.
typicalUnitSize
Indicates the standard or most common size or quantity in which something is typically measured, packaged, or used.
- 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_69b34543f06c8190915ebb1a4574ffa9 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b34fcc383c81908e17da7cbc86a630 |
completed | March 12, 2026, 11:44 p.m. |
| PD | Predicate disambiguation | batch_69b347f8dcb08190a725c1f7fb5a7466 |
completed | March 12, 2026, 11:10 p.m. |
Created at: March 12, 2026, 11:07 p.m.