Triple
T27295882
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jerome Eugene Morrow |
E688762
|
entity |
| Predicate | causeOfParalysis |
P11973
|
FINISHED |
| Object | car accident |
—
|
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: car accident | Statement: [Jerome Eugene Morrow, causeOfParalysis, car accident]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: causeOfParalysis Context triple: [Jerome Eugene Morrow, causeOfParalysis, car accident]
-
A.
causeOfDisability
chosen
Indicates that one entity is the reason or source that brings about another entity’s disability.
-
B.
causeOfWeakness
Indicates that one entity is the reason or source that brings about the weakness of another entity.
-
C.
lossOfFunctionPhenotype
Indicates that when a gene or gene product loses its normal function, a specific observable phenotype or trait results.
-
D.
lossOfFunctionLeadsTo
Indicates that when the function of one entity is reduced or eliminated, it causes or results in a specific effect or outcome in another entity or system.
-
E.
causeOf
Indicates that one entity brings about, produces, or is responsible for the occurrence or existence of another entity or event.
- 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_69ef355a96308190a2bed991525fb278 |
completed | April 27, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69f6a8df16a88190a23820e64a3b1f92 |
completed | May 3, 2026, 1:46 a.m. |
| PD | Predicate disambiguation | batch_69f6a751d5e48190a77dcecbe7ef9f0b |
completed | May 3, 2026, 1:39 a.m. |
Created at: April 27, 2026, 11:18 a.m.