Triple
T5979851
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arms of the Archbishop of York |
E133090
|
entity |
| Predicate | hasTypeOfCross |
P67845
|
FINISHED |
| Object | cross paty fitchy |
—
|
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: cross paty fitchy | Statement: [Arms of the Archbishop of York, hasTypeOfCross, cross paty fitchy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypeOfCross Context triple: [Arms of the Archbishop of York, hasTypeOfCross, cross paty fitchy]
-
A.
hasCross
Indicates that one entity possesses, displays, or is marked by a cross in relation to another entity or context.
-
B.
crossType
Indicates a relationship where one entity intersects, passes over, or traverses another, typically implying movement or extension across a boundary, area, or medium.
-
C.
hasNumberOfCrosses
Indicates the quantity of crosses associated with or present on a given entity.
-
D.
hasCrossColor
Indicates that an entity possesses a cross-shaped marking or pattern of a specified color.
-
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. 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_69c0086f45e8819098f73dd16d45ec9d |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c04dc2243c8190bd3488e7b24af985 |
completed | March 22, 2026, 8:14 p.m. |
| PD | Predicate disambiguation | batch_69c049dcb3c081908ccc9b4d4b210229 |
completed | March 22, 2026, 7:58 p.m. |
| PDg | Predicate description generation | batch_69c04dbefd1081909795fe1a812b991a |
completed | March 22, 2026, 8:14 p.m. |
Created at: March 22, 2026, 4:04 p.m.