Triple
T959075
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rosemary Kennedy |
E20692
|
entity |
| Predicate | causeOfDisabilityWorsening |
P11973
|
FINISHED |
| Object | lobotomy |
—
|
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: lobotomy | Statement: [Rosemary Kennedy, causeOfDisabilityWorsening, lobotomy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: causeOfDisabilityWorsening Context triple: [Rosemary Kennedy, causeOfDisabilityWorsening, lobotomy]
-
A.
causeOfDisability
chosen
Indicates that one entity is the reason or source that brings about another entity’s disability.
-
B.
disability
Indicates that an entity has a physical, mental, or sensory impairment that substantially limits one or more major life activities.
-
C.
causeOfInjury
Indicates that one entity is the source or reason that another entity sustained an injury.
-
D.
causeOf
Indicates that one entity brings about, produces, or is responsible for the occurrence or existence of another entity or event.
-
E.
eraOfIncreasedIntensity
Indicates a period during which the level or strength of a particular activity, condition, or phenomenon becomes significantly higher than before.
- 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_69a493b21f2881908132dcf45dcd2f36 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4b3fc94ec8190b55c6cdf3a37d6b5 |
completed | March 1, 2026, 9:47 p.m. |
| PD | Predicate disambiguation | batch_69a4b2a18ecc8190883f6206fe3b0fb6 |
completed | March 1, 2026, 9:41 p.m. |
Created at: March 1, 2026, 7:40 p.m.