Triple
T2192574
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Coat of arms of Groningen (province) |
E49895
|
entity |
| Predicate | featuresCrossColor |
P8396
|
FINISHED |
| Object | green 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: green cross | Statement: [Coat of arms of Groningen (province), featuresCrossColor, green cross]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresCrossColor Context triple: [Coat of arms of Groningen (province), featuresCrossColor, green cross]
-
A.
featuresCross
Indicates that one feature or element intersects or passes across another in space or structure.
-
B.
hasCrossColor
chosen
Indicates that an entity possesses a cross-shaped marking or pattern of a specified color.
-
C.
featuresCrossoverWith
Indicates that one entity includes or participates in a crossover event or collaboration with another entity.
-
D.
colorVarietyOf
Indicates that one entity represents a specific color variant or color option of another entity.
-
E.
colors
Indicates that one entity assigns, describes, or provides the color or colors of 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_69a88aaba3c48190b351cab9b26989ff |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abbf48ceb48190956df39377df0548 |
completed | March 7, 2026, 6:01 a.m. |
| PD | Predicate disambiguation | batch_69abbda52328819089c7ab111bebb0ca |
completed | March 7, 2026, 5:54 a.m. |
Created at: March 4, 2026, 7:46 p.m.