Triple
T32876008
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Erasmus Craven |
E840929
|
entity |
| Predicate | spouseStatusInStory |
P5173
|
FINISHED |
| Object | believed dead at start of film |
—
|
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: believed dead at start of film | Statement: [Erasmus Craven, spouseStatusInStory, believed dead at start of film]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: spouseStatusInStory Context triple: [Erasmus Craven, spouseStatusInStory, believed dead at start of film]
-
A.
hasSpouseInStory
Indicates that one entity is depicted as the spouse of another within the context of a particular story or narrative.
-
B.
spouseStatus
chosen
Indicates the marital relationship status between two individuals, such as whether they are currently spouses, formerly spouses, or not married to each other.
-
C.
socialStatusOfSpouse
Indicates the social status or rank held by a person's spouse within a given social or cultural context.
-
D.
hasSpouseDescribed
Indicates that one entity is described as the spouse of another entity.
-
E.
spouseAssociatedWith
Indicates a marital or spousal relationship or close association between two entities.
- 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_69f349436ee88190b72ee12d0f3f508e |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69fd9ff026a48190bfec33deeb3b2c43 |
completed | May 8, 2026, 8:33 a.m. |
| PD | Predicate disambiguation | batch_69fd97d805bc8190ba12f429d3ad04c7 |
completed | May 8, 2026, 7:59 a.m. |
Created at: May 1, 2026, 1:18 a.m.