Triple
T11377884
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Charlie Graham |
E269515
|
entity |
| Predicate | causeOfDeathInFilm |
P90208
|
FINISHED |
| Object | decapitation in 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: decapitation in car accident | Statement: [Charlie Graham, causeOfDeathInFilm, decapitation in car accident]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: causeOfDeathInFilm Context triple: [Charlie Graham, causeOfDeathInFilm, decapitation in car accident]
-
A.
causeOfDeath
Indicates the specific factor, event, or condition that directly resulted in an entity’s death.
-
B.
reasonForDeath
Indicates the cause, circumstance, or condition that led to an entity’s death.
-
C.
deathTypeInFiction
chosen
Indicates the manner or category of how a character dies within a fictional narrative.
-
D.
namedAfterCauseOfDeath
Indicates that an entity is named after the cause of death of a person or organism.
-
E.
deathInFiction
Indicates that an entity’s death occurs within a fictional work or narrative rather than in real life.
- 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_69d6aacca1048190b39dbbc2174616fa |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d800160a1c81909d115bf89fe54a49 |
completed | April 9, 2026, 7:37 p.m. |
| PD | Predicate disambiguation | batch_69d7e7022d508190996f9be0847c2b41 |
completed | April 9, 2026, 5:50 p.m. |
Created at: April 8, 2026, 9:33 p.m.