Triple
T7252872
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Most Holy Place |
E157645
|
entity |
| Predicate | tabernacleDimensions |
P26940
|
FINISHED |
| Object | 10 cubits by 10 cubits by 10 cubits (according to many reconstructions) |
—
|
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: 10 cubits by 10 cubits by 10 cubits (according to many reconstructions) | Statement: [Most Holy Place, tabernacleDimensions, 10 cubits by 10 cubits by 10 cubits (according to many reconstructions)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: tabernacleDimensions Context triple: [Most Holy Place, tabernacleDimensions, 10 cubits by 10 cubits by 10 cubits (according to many reconstructions)]
-
A.
typicalDimension
Indicates that one entity represents a standard or characteristic measurement (such as size, length, or capacity) typically associated with another entity.
-
B.
cabinWidth
Indicates the measurement of how wide a cabin is across its interior.
-
C.
interiorSize
chosen
Indicates the size or dimensions of the inside space of an object or structure.
-
D.
atriumHeight
Indicates the vertical measurement of an atrium from its floor to its ceiling or highest point.
-
E.
cabinWidthM
Indicates the width of a cabin measured in meters.
- 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_69c6882d81d4819085f7ff862951ee4f |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6ea9d41908190bb76c6a5b9d5b1a2 |
completed | March 27, 2026, 8:37 p.m. |
| PD | Predicate disambiguation | batch_69c6e7666ffc81908bf643d8257e6337 |
completed | March 27, 2026, 8:24 p.m. |
Created at: March 27, 2026, 2:56 p.m.