Triple
T1978163
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Christ of Saint John of the Cross |
E42962
|
entity |
| Predicate | hasNoDepictionOf |
P33022
|
FINISHED |
| Object | crown of thorns |
—
|
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: crown of thorns | Statement: [Christ of Saint John of the Cross, hasNoDepictionOf, crown of thorns]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNoDepictionOf Context triple: [Christ of Saint John of the Cross, hasNoDepictionOf, crown of thorns]
-
A.
canBeDepictedAs
Indicates that one entity is capable of being visually represented or illustrated in the form or style of another entity.
-
B.
depictsPerson
Indicates that one entity visually represents or portrays a specific person.
-
C.
depictionType
Indicates the specific manner or style in which something is visually represented or depicted.
-
D.
depictsNationality
Indicates that one entity visually represents or portrays the nationality or national identity of another entity.
-
E.
artisticDepiction
Indicates that one entity visually represents, portrays, or illustrates another in an artistic medium.
- 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_69a8871289048190b00b0d7744b7b2b1 |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abb42ecde881909bc9132885d8d0bd |
completed | March 7, 2026, 5:14 a.m. |
| PD | Predicate disambiguation | batch_69abaff9a09c8190a81fa13f4b85bc79 |
completed | March 7, 2026, 4:56 a.m. |
| PDg | Predicate description generation | batch_69abb09b27e88190bff164040fef6d7e |
completed | March 7, 2026, 4:59 a.m. |
Created at: March 4, 2026, 7:36 p.m.