Triple
T20063607
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Clair Engle |
E499547
|
entity |
| Predicate | wasAfflictedBy |
P91920
|
FINISHED |
| Object | brain cancer during Senate service |
—
|
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: brain cancer during Senate service | Statement: [Clair Engle, wasAfflictedBy, brain cancer during Senate service]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wasAfflictedBy Context triple: [Clair Engle, wasAfflictedBy, brain cancer during Senate service]
-
A.
hadCondition
Indicates that an entity experienced or was diagnosed with a particular medical or health-related condition.
-
B.
isVictimOf
Indicates that one entity suffers harm, loss, or wrongdoing as a result of another entity’s actions or events.
-
C.
sufferedCondition
chosen
Indicates that an entity experienced or was afflicted by a particular condition, typically adverse or harmful, at some point in time.
-
D.
curedWith
Indicates that one entity is treated or healed by using another entity as the remedy or therapeutic method.
-
E.
wrongedBy
Indicates that one entity has been harmed, treated unjustly, or suffered a grievance as a result of another entity's actions.
- 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_69da6276bcf48190aabbf279192a5fb4 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e66377b6b48190a0a37279f285123e |
completed | April 20, 2026, 5:33 p.m. |
| PD | Predicate disambiguation | batch_69e54cee7a5c819084ae4ff26419833f |
completed | April 19, 2026, 9:45 p.m. |
Created at: April 11, 2026, 3:39 p.m.