Triple
T8330149
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Codex Laudianus (E 08) |
E195053
|
entity |
| Predicate | approximateNumberOfLeaves |
P23586
|
FINISHED |
| Object | about 227 leaves |
—
|
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: about 227 leaves | Statement: [Codex Laudianus (E 08), approximateNumberOfLeaves, about 227 leaves]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: approximateNumberOfLeaves Context triple: [Codex Laudianus (E 08), approximateNumberOfLeaves, about 227 leaves]
-
A.
hasApproximateLeaves
Indicates that one entity possesses a number of leaves that is approximately equal to the number of leaves of another entity.
-
B.
currentNumberOfLeaves
Indicates the present count of leaves associated with an entity at a given point in time.
-
C.
originalNumberOfLeaves
Indicates the initial count of leaves associated with an entity before any changes, losses, or additions occur.
-
D.
numberOfLeaflets
Indicates the count of individual leaflets associated with or contained within a given entity.
-
E.
numberOfLeaves
chosen
Indicates the specific count of leaves associated with an 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_69ca82e87f2c8190bdb71ee29dfc642d |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb7fb995508190b2ca94ad45bf6d24 |
completed | March 31, 2026, 8:03 a.m. |
| PD | Predicate disambiguation | batch_69cb70c3231c81909e3d463192c9de22 |
completed | March 31, 2026, 6:59 a.m. |
Created at: March 30, 2026, 5:56 p.m.