Triple
T27420159
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lee Marvin as Vince Stone |
E693018
|
entity |
| Predicate | victimInNotableScene |
P6323
|
FINISHED |
| Object | Debby Marsh |
E1773061
|
NE 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: Debby Marsh | Statement: [Lee Marvin as Vince Stone, victimInNotableScene, Debby Marsh]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: victimInNotableScene Context triple: [Lee Marvin as Vince Stone, victimInNotableScene, Debby Marsh]
-
A.
victimDiedIn
Indicates that the victim lost their life as a result of, or during the course of, the referenced event or circumstance.
-
B.
notableVictim
Indicates that the subject is a person or entity who is notably recognized as a victim of the object (such as an event, crime, or harmful action).
-
C.
victimRole
Indicates that one entity participates in an event or situation specifically in the role of the victim or harmed party.
-
D.
victimCharacter
Indicates that one entity is the victim or target of harm, wrongdoing, or an adverse action carried out by another entity.
-
E.
portraysAsVictim
chosen
Indicates that one entity represents or depicts another entity as a victim in a given context or narrative.
- F. None of above.
Provenance (4 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_69ef5208617081908f731d312e0fd1bc |
completed | April 27, 2026, 12:09 p.m. |
| NER | Named-entity recognition | batch_69f65a6c900881908f18b61273d7bf8d |
completed | May 2, 2026, 8:11 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a12bbd14b3081908dd5e5404e184a43 |
completed | May 24, 2026, 8:50 a.m. |
| PD | Predicate disambiguation | batch_69f659ce58408190ba9e007b4810d4d0 |
completed | May 2, 2026, 8:08 p.m. |
Created at: April 27, 2026, 12:35 p.m.