Triple
T16017894
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arms of the Most Venerable Order of the Hospital of Saint John of Jerusalem |
E388514
|
entity |
| Predicate | crossColour |
P8396
|
FINISHED |
| Object | white |
—
|
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: white | Statement: [Arms of the Most Venerable Order of the Hospital of Saint John of Jerusalem, crossColour, white]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: crossColour Context triple: [Arms of the Most Venerable Order of the Hospital of Saint John of Jerusalem, crossColour, white]
-
A.
crossColorOutcome
Indicates the resulting color or color-related effect produced when two or more colors are combined, interacted, or crossed.
-
B.
crossWith
Indicates that one entity intersects or passes over/through the path, boundary, or position of another entity.
-
C.
crossTincture
Indicates that one entity bears or displays a cross whose tincture (heraldic color or pattern) is specified or characterized in relation to another entity.
-
D.
hasCrossColor
chosen
Indicates that an entity possesses a cross-shaped marking or pattern of a specified color.
-
E.
crossedBy
Indicates that one entity (typically a path, line, or boundary) is intersected or traversed by another entity.
- 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_69d86dabcb7c8190b6a39d6831d2fa1b |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e1858a00888190b8505071575dc56f |
completed | April 17, 2026, 12:57 a.m. |
| PD | Predicate disambiguation | batch_69e1826a4f7c8190aba6d4f1075141b0 |
completed | April 17, 2026, 12:44 a.m. |
Created at: April 10, 2026, 4:55 a.m.