Triple
T7103907
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | St John’s Cross (replica on site) |
E165526
|
entity |
| Predicate | hasCrossType |
P67845
|
FINISHED |
| Object | ringed high cross |
—
|
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: ringed high cross | Statement: [St John’s Cross (replica on site), hasCrossType, ringed high cross]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCrossType Context triple: [St John’s Cross (replica on site), hasCrossType, ringed high cross]
-
A.
hasTypeOfCross
chosen
Indicates that an entity possesses or is associated with a specific type or style of cross.
-
B.
hasCross
Indicates that one entity possesses, displays, or is marked by a cross in relation to another entity or context.
-
C.
hasCrossColor
Indicates that an entity possesses a cross-shaped marking or pattern of a specified color.
-
D.
crossType
Indicates a relationship where one entity intersects, passes over, or traverses another, typically implying movement or extension across a boundary, area, or medium.
-
E.
crossingType
Indicates the specific kind or category of crossing (e.g., how or where one thing passes over, through, or across another).
- 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_69c6887fcddc8190a5d58908f6dee590 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e58b3f708190bebca7d4c4db40f2 |
completed | March 27, 2026, 8:16 p.m. |
| PD | Predicate disambiguation | batch_69c6e1c313e481908b61a23fc89f9332 |
completed | March 27, 2026, 8 p.m. |
Created at: March 27, 2026, 2:42 p.m.