Triple
T16798635
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Christ fallen under the Cross |
E408296
|
entity |
| Predicate | oftenShows |
P2371
|
FINISHED |
| Object | Christ kneeling or lying on the ground |
—
|
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: Christ kneeling or lying on the ground | Statement: [Christ fallen under the Cross, oftenShows, Christ kneeling or lying on the ground]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: oftenShows Context triple: [Christ fallen under the Cross, oftenShows, Christ kneeling or lying on the ground]
-
A.
showsThat
Indicates that one entity demonstrates, proves, or provides evidence for the truth or validity of another.
-
B.
shows
chosen
Indicates that one entity presents, displays, or makes another entity visible or known to an audience or observer.
-
C.
associatedShow
Indicates a relationship where one entity is linked or connected to a particular show (e.g., as its subject, source, or related program).
-
D.
notableShow
Indicates that a show is especially prominent, distinguished, or significant in some noteworthy way.
-
E.
associatedShowType
Indicates a relationship where one entity is linked to the type or category of show with which it is associated.
- 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_69d88393905081908d00a86b99996ac8 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e3b2abc430819080c1303eded5f416 |
completed | April 18, 2026, 4:34 p.m. |
| PD | Predicate disambiguation | batch_69e319d0fdb8819088425bd82431640f |
completed | April 18, 2026, 5:42 a.m. |
Created at: April 10, 2026, 5:22 a.m.