Triple
T25486139
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Daniel Wayne Smith |
E638713
|
entity |
| Predicate | deathOccurredWhile |
P59930
|
FINISHED |
| Object | visiting his mother in the hospital after the birth of his half-sister |
—
|
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: visiting his mother in the hospital after the birth of his half-sister | Statement: [Daniel Wayne Smith, deathOccurredWhile, visiting his mother in the hospital after the birth of his half-sister]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: deathOccurredWhile Context triple: [Daniel Wayne Smith, deathOccurredWhile, visiting his mother in the hospital after the birth of his half-sister]
-
A.
diedWhile
Indicates that one entity ceased to live during the occurrence or performance of another specified event or activity.
-
B.
deathOutcome
Indicates that an event, condition, or action results in the death of the affected entity.
-
C.
deathResultedIn
Indicates that one event, action, or condition caused or led directly to a particular death as its outcome.
-
D.
deathDuringEvent
chosen
Indicates that an entity died while a specified event was occurring.
-
E.
deathApprox
Indicates that an entity’s death occurred at an approximate, rather than exact, time or date.
- 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_69e75dbabeac8190bab30628f8b799d4 |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f5f77c4cfc819097efb731d25b3452 |
completed | May 2, 2026, 1:09 p.m. |
| PD | Predicate disambiguation | batch_69f5afd5baac8190bb8ed576813c8591 |
completed | May 2, 2026, 8:03 a.m. |
Created at: April 21, 2026, 2:32 p.m.