Triple
T28889410
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lifeboat Carpathia (as depicted in film) |
E732655
|
entity |
| Predicate | rescuesCharacter |
P7320
|
FINISHED |
| Object | Rose DeWitt Bukater |
—
|
NE NERFINISHED |
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: Rose DeWitt Bukater | Statement: [Lifeboat Carpathia (as depicted in film), rescuesCharacter, Rose DeWitt Bukater]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: rescuesCharacter Context triple: [Lifeboat Carpathia (as depicted in film), rescuesCharacter, Rose DeWitt Bukater]
-
A.
seeksToRescue
Indicates an entity’s intention or effort to save or free another entity from danger, harm, or an undesirable situation.
-
B.
rescuesWith
Indicates that one entity saves or frees another entity from danger, harm, or captivity using a particular means, tool, or method.
-
C.
rescuesFrom
Indicates that one entity saves or frees another entity from a dangerous, harmful, or undesirable situation or source.
-
D.
rescuedBy
chosen
Indicates that one entity has been saved or brought out of danger by another entity.
-
E.
rescuedTo
Indicates that one entity has been saved or freed from danger, harm, or a problematic situation and brought to the safety or custody of another entity or location.
- 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_69f05b07bdec819080cadfe147aa1f25 |
completed | April 28, 2026, 7 a.m. |
| NER | Named-entity recognition | batch_69f6617ba4a88190bfc5c305acb4f93f |
completed | May 2, 2026, 8:41 p.m. |
| PD | Predicate disambiguation | batch_69f660f082508190a95a7888ad66cb2e |
completed | May 2, 2026, 8:39 p.m. |
Created at: April 28, 2026, 7:53 a.m.