Triple
T23203757
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dirty Kanza |
E580387
|
entity |
| Predicate | hasMultipleDistances |
P151338
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Dirty Kanza, hasMultipleDistances, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMultipleDistances Context triple: [Dirty Kanza, hasMultipleDistances, yes]
-
A.
hasDistanceCategory
Indicates that one entity is associated with a qualitative or categorical classification of its distance relative to another entity or reference point.
-
B.
numberOfDistances
Indicates the count of distinct distance values associated with or measured between entities in a given context.
-
C.
hasWellMeasuredDistances
Indicates that accurate and reliable distance measurements have been obtained between the related entities.
-
D.
hasDistanceReference
Indicates that a distance value is specified relative to a particular reference point, scale, or standard.
-
E.
hasDistanceUnit
Indicates that a specified unit of measurement is used to express a distance value in the relationship.
- 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_69e24602ae1481908aaa6bc7ca493867 |
completed | April 17, 2026, 2:38 p.m. |
| NER | Named-entity recognition | batch_69f1907b3e88819088a397a99456bf77 |
completed | April 29, 2026, 5 a.m. |
| PD | Predicate disambiguation | batch_69effcccee508190a7ae311fdd319806 |
completed | April 28, 2026, 12:18 a.m. |
| PDg | Predicate description generation | batch_69f01d8770d081908897c28b04e5faea |
completed | April 28, 2026, 2:37 a.m. |
Created at: April 17, 2026, 4:07 p.m.