Triple
T32189511
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hartigan suffers from a heart condition |
E822198
|
entity |
| Predicate | increasesRiskOf |
P149293
|
FINISHED |
| Object | John Hartigan's death |
—
|
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: John Hartigan's death | Statement: [Hartigan suffers from a heart condition, increasesRiskOf, John Hartigan's death]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: increasesRiskOf Context triple: [Hartigan suffers from a heart condition, increasesRiskOf, John Hartigan's death]
-
A.
hasRiskFrom
Indicates that one entity is exposed to or may suffer potential harm, loss, or adverse effects as a result of another entity.
-
B.
riskIfTooHigh
Indicates that a certain level or value becomes risky or dangerous when it exceeds a specified threshold.
-
C.
hasRiskFactorFor
chosen
Indicates that one entity contributes to or increases the likelihood of another entity experiencing a particular risk or adverse outcome.
-
D.
riskTakenFor
Indicates that one entity accepts or undertakes a risk for the benefit, protection, or sake of another entity.
-
E.
riskElement
Indicates that one entity is a risk-related component, factor, or contributor associated with another entity within a risk 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_69f3490819cc81909bae1f8ce99423c5 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6bacbaa208190b1edec2032701044 |
completed | May 3, 2026, 3:02 a.m. |
| PD | Predicate disambiguation | batch_69f6b3aa892481908d29283a074e6722 |
completed | May 3, 2026, 2:32 a.m. |
Created at: May 1, 2026, 12:35 a.m.