Triple
T27295879
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jerome Eugene Morrow |
E688762
|
entity |
| Predicate | goalBeforeAccident |
P162312
|
FINISHED |
| Object | compete in elite swimming |
—
|
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: compete in elite swimming | Statement: [Jerome Eugene Morrow, goalBeforeAccident, compete in elite swimming]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: goalBeforeAccident Context triple: [Jerome Eugene Morrow, goalBeforeAccident, compete in elite swimming]
-
A.
accidentOccurredDuring
Indicates that an accident took place within the time span or context of a specified event, activity, or condition.
-
B.
intendedDestinationAtAccident
Indicates that a location was the destination an entity was heading toward at the time an accident occurred.
-
C.
goalAtEnd
Indicates that a particular goal or objective holds true or is achieved at the final state or endpoint of a process, sequence, or event.
-
D.
hasAccidentAt
Indicates that an accident involving a subject occurs at a specific location or time.
-
E.
safetyGoal
Indicates that an entity is associated with a specific safety objective or target condition intended to prevent harm or reduce risk.
- 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_69ef355a96308190a2bed991525fb278 |
completed | April 27, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69f6277ff9848190958c203e511b1393 |
completed | May 2, 2026, 4:34 p.m. |
| PD | Predicate disambiguation | batch_69f620e38aec8190bb184edcdbd6da64 |
completed | May 2, 2026, 4:05 p.m. |
| PDg | Predicate description generation | batch_69f622a8fe7c819096e8a43db263a423 |
completed | May 2, 2026, 4:13 p.m. |
Created at: April 27, 2026, 11:18 a.m.