Triple
T5984537
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ben Johnson 100 metres disqualification |
E133193
|
entity |
| Predicate | sampleResult |
P58414
|
FINISHED |
| Object | positive for anabolic steroids |
—
|
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: positive for anabolic steroids | Statement: [Ben Johnson 100 metres disqualification, sampleResult, positive for anabolic steroids]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sampleResult Context triple: [Ben Johnson 100 metres disqualification, sampleResult, positive for anabolic steroids]
-
A.
sampleSize
Indicates the number of units, observations, or instances included in a particular study, experiment, or dataset.
-
B.
testResult
chosen
Indicates that an entity has produced a specific outcome or value when subjected to a particular test or evaluation.
-
C.
samplesWork
Indicates that one entity takes or obtains a sample of another entity’s work for examination, testing, or evaluation.
-
D.
result
Indicates that one entity is produced, caused, or brought about as an outcome or consequence of another entity or process.
-
E.
resultUsage
Indicates how the outcome or result of an action, process, or event is used, applied, or consumed in relation to another entity or context.
- 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_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. |
Created at: March 22, 2026, 4:04 p.m.