Triple
T13530514
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vierdaagsekruis |
E323119
|
entity |
| Predicate | minimumDistance |
P84306
|
FINISHED |
| Object | varies by age and category |
—
|
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: varies by age and category | Statement: [Vierdaagsekruis, minimumDistance, varies by age and category]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: minimumDistance Context triple: [Vierdaagsekruis, minimumDistance, varies by age and category]
-
A.
minimumRange
chosen
Indicates the smallest allowable or observed value within a specified range for a given relationship or measurement.
-
B.
minimumDistanceRequirement
Indicates that there is a required minimum distance that must be maintained between the related entities.
-
C.
minimumNumber
Indicates that the associated value is the smallest or least quantity allowed, required, or observed within a given set or context.
-
D.
numberOfDistances
Indicates the count of distinct distance values associated with or measured between entities in a given context.
-
E.
shortestNear
Indicates that one entity is the closest (or among the closest) to another entity compared to other nearby alternatives.
- 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_69d80766a21881909f21a1b7421d3b8a |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbafba2c308190873efd15dfe26358 |
completed | April 12, 2026, 2:44 p.m. |
| PD | Predicate disambiguation | batch_69dbae1046c48190b4ee98c6c9cb9d85 |
completed | April 12, 2026, 2:37 p.m. |
Created at: April 9, 2026, 9:44 p.m.