Triple
T2192575
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Coat of arms of Groningen (province) |
E49895
|
entity |
| Predicate | featuresCrossShape |
P36674
|
FINISHED |
| Object | Greek 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: Greek cross | Statement: [Coat of arms of Groningen (province), featuresCrossShape, Greek cross]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresCrossShape Context triple: [Coat of arms of Groningen (province), featuresCrossShape, Greek cross]
-
A.
featuresCross
Indicates that one feature or element intersects or passes across another in space or structure.
-
B.
featuresCrossoverWith
Indicates that one entity includes or participates in a crossover event or collaboration with another entity.
-
C.
crossesIn
Indicates that one entity passes over or through the path, boundary, or area occupied by another entity, intersecting its space or trajectory.
-
D.
crossesSectionOf
Indicates that one entity passes through or over a specific segment or portion of another entity.
-
E.
coreShape
Indicates that one entity serves as the primary or central shape or geometric form of another entity.
- 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_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. |
| PDg | Predicate description generation | batch_69abbea8bd4881908f72019a5acf6174 |
completed | March 7, 2026, 5:59 a.m. |
Created at: March 4, 2026, 7:46 p.m.