Triple
T19108391
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | James Cagney as Eddie Bartlett |
E467719
|
entity |
| Predicate | characterFate |
P24728
|
FINISHED |
| Object | diesAtEndOfFilm |
—
|
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: diesAtEndOfFilm | Statement: [James Cagney as Eddie Bartlett, characterFate, diesAtEndOfFilm]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: characterFate Context triple: [James Cagney as Eddie Bartlett, characterFate, diesAtEndOfFilm]
-
A.
hasDifferentFateOfCharacter
Indicates that two characters experience distinct outcomes or destinies within a narrative or scenario.
-
B.
eventualFate
chosen
Indicates the ultimate outcome or final state that an entity is destined to reach over time.
-
C.
chosenFate
Indicates that an entity has actively selected or accepted a particular destiny or outcome, rather than having it imposed by external forces.
-
D.
character1
Indicates that the subject is identified as the first or primary character in a narrative or context.
-
E.
character2
Indicates that a second character entity is involved in the relationship or context defined by the predicate.
- 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_69d8dd06a26481908039e2a1bae8c597 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5e391f00c8190881a5977dd3728ed |
completed | April 20, 2026, 8:28 a.m. |
| PD | Predicate disambiguation | batch_69e4b9ac41848190afd0f33b42cebe99 |
completed | April 19, 2026, 11:17 a.m. |
Created at: April 10, 2026, 12:04 p.m.