Triple
T14997449
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Saint Dismas |
E373993
|
entity |
| Predicate | traditionalSideOfCross |
P116277
|
FINISHED |
| Object | right side of Jesus |
—
|
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: right side of Jesus | Statement: [Saint Dismas, traditionalSideOfCross, right side of Jesus]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: traditionalSideOfCross Context triple: [Saint Dismas, traditionalSideOfCross, right side of Jesus]
-
A.
traditionalCrossType
Indicates that one entity is related to another through a conventional or historically established type of cross or crossing relationship.
-
B.
crossesIn
Indicates that one entity passes over or through the path, boundary, or area occupied by another entity, intersecting its space or trajectory.
-
C.
crossesTo
Indicates that one entity moves or extends from one side or area to another, passing over or through some boundary or intervening space.
-
D.
orientationOfCross
Indicates the spatial orientation or alignment of a cross relative to a reference frame or object.
-
E.
doubleCrosses
Indicates that one party betrays another by secretly switching allegiance or undermining them after initially appearing loyal.
- F. None of above. chosen
Provenance (4 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_69d85ccc84388190aa151e5173370c8d |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded718e4288190b5e144f82299a194 |
completed | April 15, 2026, 12:08 a.m. |
| PD | Predicate disambiguation | batch_69de9a6169b48190a679609febd2d0e3 |
completed | April 14, 2026, 7:49 p.m. |
| PDg | Predicate description generation | batch_69deb1a88d588190996afa8e5b32b552 |
completed | April 14, 2026, 9:29 p.m. |
Created at: April 10, 2026, 2:54 a.m.