Triple
T19094047
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Disputation with the Doctors |
E467359
|
entity |
| Predicate | typicalFigureCount |
P6685
|
FINISHED |
| Object | Jesus and several elders |
—
|
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: Jesus and several elders | Statement: [Disputation with the Doctors, typicalFigureCount, Jesus and several elders]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalFigureCount Context triple: [Disputation with the Doctors, typicalFigureCount, Jesus and several elders]
-
A.
typicalFigure
Indicates that one entity serves as a standard or representative example (a typical instance) of the other entity.
-
B.
numberOfFiguresDepicted
chosen
Indicates the total count of distinct figures shown within a given depiction or representation.
-
C.
numberOfBronzeFigures
Indicates the quantity of bronze figures associated with a given subject or context.
-
D.
largestFigureLengthApprox
Indicates an approximate measurement of the length of the largest figure involved in the relationship or context.
-
E.
typicalDimension
Indicates that one entity represents a standard or characteristic measurement (such as size, length, or capacity) typically associated with 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_69d8dd05ac4c8190b1967d8f97f3fb2f |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5e34e1ee0819092f679d916e6e532 |
completed | April 20, 2026, 8:26 a.m. |
| PD | Predicate disambiguation | batch_69e4b9a604308190a3235184f9f2c056 |
completed | April 19, 2026, 11:16 a.m. |
Created at: April 10, 2026, 12:04 p.m.