Triple
T13079312
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Henleigh Grandcourt |
E310159
|
entity |
| Predicate | deathSceneInvolves |
P34448
|
FINISHED |
| Object | a boating 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: a boating accident | Statement: [Henleigh Grandcourt, deathSceneInvolves, a boating accident]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: deathSceneInvolves Context triple: [Henleigh Grandcourt, deathSceneInvolves, a boating accident]
-
A.
deathSceneWork
chosen
Indicates that a creative work features or depicts the scene in which a character dies.
-
B.
deathBy
Indicates a relationship where one entity’s death is caused by another entity, event, or factor.
-
C.
deathOutcome
Indicates that an event, condition, or action results in the death of the affected entity.
-
D.
deathApprox
Indicates that an entity’s death occurred at an approximate, rather than exact, time or date.
-
E.
deathResultedIn
Indicates that one event, action, or condition caused or led directly to a particular death as its outcome.
- 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_69d806a733548190989cfd4ce981ca33 |
completed | April 9, 2026, 8:05 p.m. |
| NER | Named-entity recognition | batch_69d98119cb7081908b78ffe83ec99851 |
completed | April 10, 2026, 11 p.m. |
| PD | Predicate disambiguation | batch_69d9803d46688190bac6b7d208f08d01 |
completed | April 10, 2026, 10:57 p.m. |
Created at: April 9, 2026, 9:01 p.m.