Triple
T35856000
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Frank Sinatra as Barney Sloan |
E1036504
|
entity |
| Predicate | survivesByEndOfFilm |
P83430
|
FINISHED |
| Object | Yes |
—
|
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: Yes | Statement: [Frank Sinatra as Barney Sloan, survivesByEndOfFilm, Yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: survivesByEndOfFilm Context triple: [Frank Sinatra as Barney Sloan, survivesByEndOfFilm, Yes]
-
A.
survivesEventsOfFilm
Indicates that an entity remains alive or intact through all the events depicted in a film.
-
B.
survivesFor
Indicates that one entity continues to exist, endure, or remain functional for a specified duration or period.
-
C.
survivesBy
Indicates that one entity continues to live or exist after another entity has died or ceased to exist.
-
D.
survivesWith
Indicates that one entity continues to live, endure, or remain viable in the presence, context, or company of another entity.
-
E.
statusAtEndOfFilm
chosen
Indicates the condition or situation an entity is in when the film concludes.
- 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_69f76e1b4aa481909630373171eb5ec6 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7aa3883d48190b05e3d2da7a017ae |
completed | May 3, 2026, 8:04 p.m. |
| PD | Predicate disambiguation | batch_69f7a8d435288190b30b1991fb003121 |
completed | May 3, 2026, 7:58 p.m. |
Created at: May 3, 2026, 4:06 p.m.