Triple
T5984536
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ben Johnson 100 metres disqualification |
E133193
|
entity |
| Predicate | sampleType |
P67742
|
FINISHED |
| Object | urine |
—
|
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: urine | Statement: [Ben Johnson 100 metres disqualification, sampleType, urine]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sampleType Context triple: [Ben Johnson 100 metres disqualification, sampleType, urine]
-
A.
sampleSize
Indicates the number of units, observations, or instances included in a particular study, experiment, or dataset.
-
B.
exampleType
Indicates that one entity serves as a representative or illustrative instance of the type or category defined by another entity.
-
C.
samplingUnit
Indicates that one entity serves as the basic unit or element from which samples are drawn or measured in a sampling process.
-
D.
seeType
Indicates that one entity observes, recognizes, or visually perceives another entity of a particular type or category.
-
E.
simType
Indicates that two entities share the same or a comparable type, category, or classification.
- 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_69c0087010d081908bb8142342d63330 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c04a6c4f2481909cdcf931331b3595 |
completed | March 22, 2026, 8 p.m. |
| PD | Predicate disambiguation | batch_69c049de98648190962b14fd341c93da |
completed | March 22, 2026, 7:58 p.m. |
| PDg | Predicate description generation | batch_69c04a663a4481908983048c69cba6b6 |
completed | March 22, 2026, 8 p.m. |
Created at: March 22, 2026, 4:04 p.m.