Triple
T18271343
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eddie Olczyk |
E437620
|
entity |
| Predicate | announcedCancerDiagnosisYear |
P131125
|
FINISHED |
| Object | 2017 |
—
|
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: 2017 | Statement: [Eddie Olczyk, announcedCancerDiagnosisYear, 2017]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: announcedCancerDiagnosisYear Context triple: [Eddie Olczyk, announcedCancerDiagnosisYear, 2017]
-
A.
diagnosisYear
Indicates the calendar year in which a diagnosis was made or recorded for an entity.
-
B.
diagnosisDate
Indicates the date on which a diagnosis was formally established or recorded for an entity.
-
C.
averageSurvivalAfterDiagnosis
Indicates the typical length of time individuals survive following the point at which a condition or disease is first diagnosed.
-
D.
firstScreeningYear
Indicates the year in which an entity (such as a film or show) was first publicly screened or premiered.
-
E.
diagnosedWith
Indicates that a subject has been identified, typically by a medical professional, as having a particular disease or medical condition.
- 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_69d8b913351c8190932b6a426de04b41 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4ff7e00548190a28916a696831336 |
completed | April 19, 2026, 4:14 p.m. |
| PD | Predicate disambiguation | batch_69e44fd81c788190b08c6be3b07a08c5 |
completed | April 19, 2026, 3:45 a.m. |
| PDg | Predicate description generation | batch_69e451a0ba208190a5fe92832a8f7a49 |
completed | April 19, 2026, 3:53 a.m. |
Created at: April 10, 2026, 10:34 a.m.